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01-ai/Yi-1.5-34B
huggingface-llm-yi-1-5-34b
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference@sha256:3e3157d5d76d6fe67c08cfda5fa50d83ce5ab295b31afad54884d7d85ec047be
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-yi-1-5-34b") example_payloads = model.retrieve_...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=01-ai%2Fyi-1.5-34b&smModelId=huggingface-llm-yi-1-5-34b&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
01-ai/Yi-1.5-9B
huggingface-llm-yi-1-5-9b
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference@sha256:3e3157d5d76d6fe67c08cfda5fa50d83ce5ab295b31afad54884d7d85ec047be
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-yi-1-5-9b") example_payloads = model.retrieve_a...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=01-ai%2Fyi-1.5-9b&smModelId=huggingface-llm-yi-1-5-9b&hasVariants=false&page=deploy
null
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Alibaba-NLP/gte-Qwen2-7B-instruct
huggingface-textembedding-gte-qwen2-7b-instruct
257758044811.dkr.ecr.us-east-2.amazonaws.com/tei:2.0.1-tei1.4.0-gpu-py310-cu122-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-textembedding-gte-qwen2-7b-instruct") example_paylo...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=alibaba-nlp%2Fgte-qwen2-7b-instruct&smModelId=huggingface-textembedding-gte-qwen2-7b-instruct&hasVariants=false&page=deploy
null
null
null
null
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BAAI/bge-base-en
huggingface-sentencesimilarity-bge-base-en
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.13.1-transformers4.26.0-gpu-py39-cu117-ubuntu20.04
true
false
true
true
true
false
from sagemaker.jumpstart.model import JumpStartModel import json model_id = "huggingface-sentencesimilarity-bge-base-en" endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."]) model = JumpStartModel(model_id=model_id) predictor = model.deploy() response = predictor.predict(endpoint_input) prin...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-base-en&smModelId=huggingface-sentencesimilarity-bge-base-en&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-base-en&smModelId=huggingface-sentencesimilarity-bge-base-en&supportServerless=false&supportServerful=true&hasVariants=false&page=customize
null
null
null
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null
null
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null
BAAI/bge-base-en-v1.5
huggingface-sentencesimilarity-bge-base-en-v1-5
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.13.1-transformers4.26.0-gpu-py39-cu117-ubuntu20.04
true
false
true
true
true
false
from sagemaker.jumpstart.model import JumpStartModel import json model_id = "huggingface-sentencesimilarity-bge-base-en-v1-5" endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."]) model = JumpStartModel(model_id=model_id) predictor = model.deploy() response = predictor.predict(endpoint_input)...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-base-en-v1.5&smModelId=huggingface-sentencesimilarity-bge-base-en-v1-5&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-base-en-v1.5&smModelId=huggingface-sentencesimilarity-bge-base-en-v1-5&supportServerless=false&supportServerful=true&hasVariants=false&page=customize
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BAAI/bge-large-en
huggingface-sentencesimilarity-bge-large-en
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.13.1-transformers4.26.0-gpu-py39-cu117-ubuntu20.04
true
false
true
true
true
false
from sagemaker.jumpstart.model import JumpStartModel import json model_id = "huggingface-sentencesimilarity-bge-large-en" endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."]) model = JumpStartModel(model_id=model_id) predictor = model.deploy() response = predictor.predict(endpoint_input) pri...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-large-en&smModelId=huggingface-sentencesimilarity-bge-large-en&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-large-en&smModelId=huggingface-sentencesimilarity-bge-large-en&supportServerless=false&supportServerful=true&hasVariants=false&page=customize
null
null
null
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null
null
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null
BAAI/bge-large-en-v1.5
huggingface-sentencesimilarity-bge-large-en-v1-5
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.13.1-transformers4.26.0-gpu-py39-cu117-ubuntu20.04
true
false
true
true
true
false
from sagemaker.jumpstart.model import JumpStartModel import json model_id = "huggingface-sentencesimilarity-bge-large-en-v1-5" endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."]) model = JumpStartModel(model_id=model_id) predictor = model.deploy() response = predictor.predict(endpoint_input...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-large-en-v1.5&smModelId=huggingface-sentencesimilarity-bge-large-en-v1-5&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-large-en-v1.5&smModelId=huggingface-sentencesimilarity-bge-large-en-v1-5&supportServerless=false&supportServerful=true&hasVariants=false&page=customize
null
null
null
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null
null
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null
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null
BAAI/bge-m3
huggingface-sentencesimilarity-bge-m3
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.13.1-transformers4.26.0-gpu-py39-cu117-ubuntu20.04
true
false
true
true
true
false
from sagemaker.jumpstart.model import JumpStartModel import json model_id = "huggingface-sentencesimilarity-bge-m3" endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."]) model = JumpStartModel(model_id=model_id) predictor = model.deploy() response = predictor.predict(endpoint_input) print(f"I...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-m3&smModelId=huggingface-sentencesimilarity-bge-m3&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-m3&smModelId=huggingface-sentencesimilarity-bge-m3&supportServerless=false&supportServerful=true&hasVariants=false&page=customize
null
null
null
null
null
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null
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null
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null
BAAI/bge-small-en
huggingface-sentencesimilarity-bge-small-en
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.13.1-transformers4.26.0-gpu-py39-cu117-ubuntu20.04
true
false
true
true
true
false
from sagemaker.jumpstart.model import JumpStartModel import json model_id = "huggingface-sentencesimilarity-bge-small-en" endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."]) model = JumpStartModel(model_id=model_id) predictor = model.deploy() response = predictor.predict(endpoint_input) pri...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-small-en&smModelId=huggingface-sentencesimilarity-bge-small-en&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-small-en&smModelId=huggingface-sentencesimilarity-bge-small-en&supportServerless=false&supportServerful=true&hasVariants=false&page=customize
null
null
null
null
null
null
null
null
null
null
null
null
BAAI/bge-small-en-v1.5
huggingface-sentencesimilarity-bge-small-en-v1-5
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.13.1-transformers4.26.0-gpu-py39-cu117-ubuntu20.04
true
false
true
true
true
false
from sagemaker.jumpstart.model import JumpStartModel import json model_id = "huggingface-sentencesimilarity-bge-small-en-v1-5" endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."]) model = JumpStartModel(model_id=model_id) predictor = model.deploy() response = predictor.predict(endpoint_input...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-small-en-v1.5&smModelId=huggingface-sentencesimilarity-bge-small-en-v1-5&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baai%2Fbge-small-en-v1.5&smModelId=huggingface-sentencesimilarity-bge-small-en-v1-5&supportServerless=false&supportServerful=true&hasVariants=false&page=customize
null
null
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Bingsu/my-korean-stable-diffusion-v1-5
huggingface-txt2img-bingsu-my-korean-stable-diffusion-v1-5
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-txt2img-bingsu-my-korean-stable-diffusion-v1-5") ex...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=bingsu%2Fmy-korean-stable-diffusion-v1-5&smModelId=huggingface-txt2img-bingsu-my-korean-stable-diffusion-v1-5&hasVariants=false&page=deploy
null
null
null
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null
CohereLabs/aya-101
huggingface-llm-aya-101
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.1.1-tgi1.4.2-gpu-py310-cu121-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-aya-101") example_payloads = model.retrieve_all...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=coherelabs%2Faya-101&smModelId=huggingface-llm-aya-101&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
CohereLabs/command-a-plus-05-2026-w4a4
huggingface-vlm-command-a-plus-05-2026-w4a4
763104351884.dkr.ecr.us-east-2.amazonaws.com/sglang:0.5.18-gpu-py312-cu130-ubuntu24.04-sagemaker
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model_id = "huggingface-vlm-command-a-plus-05-2026-w4a4" model = JumpStartModel(model_id=model_...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=coherelabs%2Fcommand-a-plus-05-2026-w4a4&smModelId=huggingface-vlm-command-a-plus-05-2026-w4a4&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
EleutherAI/gpt-j-6b
huggingface-textgeneration1-gpt-j-6b
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.1.1-tgi1.4.0-gpu-py310-cu121-ubuntu20.04
true
false
true
true
true
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-textgeneration1-gpt-j-6b") example_payloads = model...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=eleutherai%2Fgpt-j-6b&smModelId=huggingface-textgeneration1-gpt-j-6b&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=eleutherai%2Fgpt-j-6b&smModelId=huggingface-textgeneration1-gpt-j-6b&supportServerless=false&supportServerful=true&hasVariants=false&page=customize
null
null
null
null
null
null
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null
null
null
EleutherAI/gpt-neo-125m
huggingface-textgeneration1-gpt-neo-125m
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.1.1-tgi1.4.0-gpu-py310-cu121-ubuntu20.04
true
false
true
true
true
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-textgeneration1-gpt-neo-125m") example_payloads = m...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=eleutherai%2Fgpt-neo-125m&smModelId=huggingface-textgeneration1-gpt-neo-125m&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=eleutherai%2Fgpt-neo-125m&smModelId=huggingface-textgeneration1-gpt-neo-125m&supportServerless=false&supportServerful=true&hasVariants=false&page=customize
null
null
null
null
null
null
null
null
null
null
null
null
EleutherAI/pythia-160m-deduped
huggingface-llm-eleutherai-pythia-160m-deduped
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi25.0.0-cu130
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-eleutherai-pythia-160m-deduped") example_payloa...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=eleutherai%2Fpythia-160m-deduped&smModelId=huggingface-llm-eleutherai-pythia-160m-deduped&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
EleutherAI/pythia-70m-deduped
huggingface-llm-eleutherai-pythia-70m-deduped
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.4.0-tgi2.4.0-gpu-py311-cu124-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-eleutherai-pythia-70m-deduped") example_payload...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=eleutherai%2Fpythia-70m-deduped&smModelId=huggingface-llm-eleutherai-pythia-70m-deduped&hasVariants=false&page=deploy
null
null
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FacebookAI/roberta-base
huggingface-eqa-roberta-base
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:2.3.0-transformers4.48.0-gpu-py311-cu121-ubuntu22.04
true
false
true
true
true
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-eqa-roberta-base") example_payloads = model.retriev...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
# Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3. # See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch import boto3 from sagemaker.train.model_trainer import ModelTrainer from sagemaker.core.training.configs import Compute, SourceCode from sagemaker.core import image_ur...
[]
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=facebookai%2Froberta-base&smModelId=huggingface-eqa-roberta-base&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=facebookai%2Froberta-base&smModelId=huggingface-eqa-roberta-base&supportServerless=false&supportServerful=true&hasVariants=false&page=customize
null
null
null
null
null
null
null
null
null
null
null
null
FacebookAI/roberta-large
huggingface-eqa-roberta-large
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:2.3.0-transformers4.48.0-gpu-py311-cu121-ubuntu22.04
true
false
true
true
true
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-eqa-roberta-large") example_payloads = model.retrie...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
# Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3. # See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch import boto3 from sagemaker.train.model_trainer import ModelTrainer from sagemaker.core.training.configs import Compute, SourceCode from sagemaker.core import image_ur...
[]
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=facebookai%2Froberta-large&smModelId=huggingface-eqa-roberta-large&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=facebookai%2Froberta-large&smModelId=huggingface-eqa-roberta-large&supportServerless=false&supportServerful=true&hasVariants=false&page=customize
null
null
null
null
null
null
null
null
null
null
null
null
Fictiverse/Stable_Diffusion_BalloonArt_Model
huggingface-txt2img-fictiverse-stable-diffusion-balloonart-model
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-txt2img-fictiverse-stable-diffusion-balloonart") ex...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=fictiverse%2Fstable_diffusion_balloonart_model&smModelId=huggingface-txt2img-fictiverse-stable-diffusion-balloonart-model&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Fictiverse/Stable_Diffusion_Microscopic_model
huggingface-txt2img-fictiverse-stable-diffusion-microscopic-model
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-txt2img-fictiverse-stable-diffusion-micro-model") e...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=fictiverse%2Fstable_diffusion_microscopic_model&smModelId=huggingface-txt2img-fictiverse-stable-diffusion-microscopic-model&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Fictiverse/Stable_Diffusion_PaperCut_Model
huggingface-txt2img-fictiverse-stable-diffusion-papercut-model
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-txt2img-fictiverse-stable-diffusion-papercut-model"...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=fictiverse%2Fstable_diffusion_papercut_model&smModelId=huggingface-txt2img-fictiverse-stable-diffusion-papercut-model&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Fictiverse/Stable_Diffusion_VoxelArt_Model
huggingface-txt2img-fictiverse-stable-diffusion-voxelart-model
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-txt2img-fictiverse-stable-diffusion-voxelart-model"...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=fictiverse%2Fstable_diffusion_voxelart_model&smModelId=huggingface-txt2img-fictiverse-stable-diffusion-voxelart-model&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Helsinki-NLP/opus-mt-en-es
huggingface-translation-opus-mt-en-es
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:2.3.0-transformers4.48.0-gpu-py311-cu121-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model_id = "huggingface-translation-opus-mt-en-es" endpoint_input = "My name is Wolfgang and I l...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=helsinki-nlp%2Fopus-mt-en-es&smModelId=huggingface-translation-opus-mt-en-es&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Helsinki-NLP/opus-mt-en-vi
huggingface-translation-opus-mt-en-vi
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:2.3.0-transformers4.48.0-gpu-py311-cu121-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model_id = "huggingface-translation-opus-mt-en-vi" endpoint_input = "My name is Wolfgang and I l...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=helsinki-nlp%2Fopus-mt-en-vi&smModelId=huggingface-translation-opus-mt-en-vi&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Helsinki-NLP/opus-mt-mul-en
huggingface-translation-opus-mt-mul-en
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model_id = "huggingface-translation-opus-mt-mul-en" endpoint_input = "My name is Wolfgang and I ...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=helsinki-nlp%2Fopus-mt-mul-en&smModelId=huggingface-translation-opus-mt-mul-en&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
HuggingFaceH4/starchat-alpha
huggingface-llm-huggingfaceh4-starchat-alpha
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.1.1-tgi1.4.0-gpu-py310-cu121-ubuntu20.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-huggingfaceh4-starchat-alpha") example_payloads...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=huggingfaceh4%2Fstarchat-alpha&smModelId=huggingface-llm-huggingfaceh4-starchat-alpha&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
HuggingFaceH4/starchat-beta
huggingface-llm-huggingfaceh4-starchat-beta
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.4.0-tgi2.4.0-gpu-py311-cu124-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-huggingfaceh4-starchat-beta") example_payloads ...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=huggingfaceh4%2Fstarchat-beta&smModelId=huggingface-llm-huggingfaceh4-starchat-beta&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
HuggingFaceH4/zephyr-7b-beta
huggingface-llm-huggingfaceh4-zephyr-7b-beta
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.1.1-tgi1.4.0-gpu-py310-cu121-ubuntu20.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-huggingfaceh4-zephyr-7b-beta") example_payloads...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=huggingfaceh4%2Fzephyr-7b-beta&smModelId=huggingface-llm-huggingfaceh4-zephyr-7b-beta&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1
huggingface-llm-huggingfaceh4-zephyr-orpo-141b-a35b-v01
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.4.0-tgi2.4.0-gpu-py311-cu124-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-huggingfaceh4-zephyr-orpo-141b-a35b-v01") examp...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=huggingfaceh4%2Fzephyr-orpo-141b-a35b-v0.1&smModelId=huggingface-llm-huggingfaceh4-zephyr-orpo-141b-a35b-v01&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-EN-v0.1
huggingface-txt2img-idea-ccnl-taiyi-stable-diffusion-1b-chinese-en-v0-1
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-txt2img-idea-ccnl-taiyi-1b-chinese-en-v01") example...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=idea-ccnl%2Ftaiyi-stable-diffusion-1b-chinese-en-v0.1&smModelId=huggingface-txt2img-idea-ccnl-taiyi-stable-diffusion-1b-chinese-en-v0-1&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
IDEA-CCNL/Taiyi-Stable-Diffusion-1B-Chinese-v0.1
huggingface-txt2img-idea-ccnl-taiyi-stable-diffusion-1b-chinese-v0-1
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-txt2img-idea-ccnl-taiyi-1b-chinese-v0-1") example_p...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=idea-ccnl%2Ftaiyi-stable-diffusion-1b-chinese-v0.1&smModelId=huggingface-txt2img-idea-ccnl-taiyi-stable-diffusion-1b-chinese-v0-1&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
JetBrains/Mellum2-12B-A2.5B-Thinking
huggingface-llm-mellum2-12b-a2-5b-thinking
763104351884.dkr.ecr.us-east-2.amazonaws.com/vllm:0.22.1-gpu-py312-cu130-ubuntu22.04-sagemaker
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-mellum2-12b-a2-5b-thinking") example_payloads =...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=jetbrains%2Fmellum2-12b-a2.5b-thinking&smModelId=huggingface-llm-mellum2-12b-a2-5b-thinking&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Langboat/Guohua-Diffusion
huggingface-txt2img-langboat-guohua-diffusion
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-txt2img-langboat-guohua-diffusion") example_payload...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=langboat%2Fguohua-diffusion&smModelId=huggingface-txt2img-langboat-guohua-diffusion&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
MiniMaxAI/MiniMax-M2
huggingface-llm-minimax-m2
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi25.0.0-cu130
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-minimax-m2") example_payloads = model.retrieve_...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=minimaxai%2Fminimax-m2&smModelId=huggingface-llm-minimax-m2&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
MiniMaxAI/MiniMax-M2.1
huggingface-llm-minimax-m2-1
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi18.0.0-cu128
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-minimax-m2-1") example_payloads = model.retriev...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=minimaxai%2Fminimax-m2.1&smModelId=huggingface-llm-minimax-m2-1&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
MiniMaxAI/MiniMax-M2.5
huggingface-llm-minimax-m2-5
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi22.0.0-cu129
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-minimax-m2-5") example_payloads = model.retriev...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=minimaxai%2Fminimax-m2.5&smModelId=huggingface-llm-minimax-m2-5&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
MiniMaxAI/MiniMax-M2.7
huggingface-llm-minimax-m2-7
763104351884.dkr.ecr.us-east-2.amazonaws.com/vllm:0.19.1-gpu-py312-cu129-ubuntu22.04-sagemaker
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-minimax-m2-7") example_payloads = model.retriev...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=minimaxai%2Fminimax-m2.7&smModelId=huggingface-llm-minimax-m2-7&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7
huggingface-zstc-moritzlaurer-mdeberta-v3-base-xnli-multilingual-nli-2mil7
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model_id = "huggingface-zstc-moritzlaurer-mdeberta3base-xnli-mling-nli-2m7" endpoint_input = {'s...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=moritzlaurer%2Fmdeberta-v3-base-xnli-multilingual-nli-2mil7&smModelId=huggingface-zstc-moritzlaurer-mdeberta-v3-base-xnli-multilingual-nli-2mil7&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Narsil/deberta-large-mnli-zero-cls
huggingface-zstc-narsil-deberta-large-mnli-zero-cls
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:1.10.2-transformers4.17.0-gpu-py38-cu113-ubuntu20.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model_id = "huggingface-zstc-narsil-deberta-large-mnli-zero-cls" endpoint_input = {'sequences': ...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=narsil%2Fdeberta-large-mnli-zero-cls&smModelId=huggingface-zstc-narsil-deberta-large-mnli-zero-cls&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
NexaAI/Octopus-v2
huggingface-llm-nexaaidev-octopus-v2
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.4.0-tgi2.4.0-gpu-py311-cu124-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-nexaaidev-octopus-v2") example_payloads = model...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=nexaai%2Foctopus-v2&smModelId=huggingface-llm-nexaaidev-octopus-v2&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Nexusflow/Starling-LM-7B-beta
huggingface-llm-nexusflow-starling-lm-7b-beta
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.1.1-tgi2.0.0-gpu-py310-cu121-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-nexusflow-starling-lm-7b-beta") example_payload...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=nexusflow%2Fstarling-lm-7b-beta&smModelId=huggingface-llm-nexusflow-starling-lm-7b-beta&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
NousResearch/Hermes-2-Pro-Llama-3-8B
huggingface-llm-nousresearch-hermes-2-pro-llama-3-8B
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.4.0-tgi2.4.0-gpu-py311-cu124-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-nousresearch-hermes-2-pro-llama-3-8B") example_...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=nousresearch%2Fhermes-2-pro-llama-3-8b&smModelId=huggingface-llm-nousresearch-hermes-2-pro-llama-3-8B&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
NousResearch/Nous-Hermes-2-SOLAR-10.7B
huggingface-llm-nousresearch-nous-hermes-2-solar-10-7b
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.4.0-tgi2.4.0-gpu-py311-cu124-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-nousresearch-nous-hermes-2-solar-10-7b") exampl...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=nousresearch%2Fnous-hermes-2-solar-10.7b&smModelId=huggingface-llm-nousresearch-nous-hermes-2-solar-10-7b&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/QVQ-72B-Preview
huggingface-vlm-qvq-72b-preview
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.4.0-tgi3.0.1-gpu-py311-cu124-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model_id = "huggingface-vlm-qvq-72b-preview" model = JumpStartModel(model_id=model_id) payload ...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqvq-72b-preview&smModelId=huggingface-vlm-qvq-72b-preview&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/QwQ-32B
huggingface-llm-qwq-32b
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.6.0-tgi3.1.1-gpu-py311-cu124-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-qwq-32b") example_payloads = model.retrieve_all...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwq-32b&smModelId=huggingface-llm-qwq-32b&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen-AgentWorld-35B-A3B
huggingface-reasoning-qwen-agentworld-35b-a3b
763104351884.dkr.ecr.us-east-2.amazonaws.com/vllm:server-sagemaker-cuda-v2
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-reasoning-qwen-agentworld-35b-a3b") example_payload...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen-agentworld-35b-a3b&smModelId=huggingface-reasoning-qwen-agentworld-35b-a3b&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen2-0.5B
huggingface-llm-qwen2-0-5b
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference@sha256:3e3157d5d76d6fe67c08cfda5fa50d83ce5ab295b31afad54884d7d85ec047be
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-qwen2-0-5b") example_payloads = model.retrieve_...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2-0.5b&smModelId=huggingface-llm-qwen2-0-5b&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen2-0.5B-Instruct
huggingface-llm-qwen2-0-5b-instruct
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference@sha256:3e3157d5d76d6fe67c08cfda5fa50d83ce5ab295b31afad54884d7d85ec047be
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-qwen2-0-5b-instruct") example_payloads = model....
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2-0.5b-instruct&smModelId=huggingface-llm-qwen2-0-5b-instruct&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen2-1.5B-Instruct
huggingface-llm-qwen2-1-5b-instruct
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi22.0.0-cu129
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-qwen2-1-5b-instruct") example_payloads = model....
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2-1.5b-instruct&smModelId=huggingface-llm-qwen2-1-5b-instruct&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen2-7B
huggingface-llm-qwen2-7b
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi18.0.0-cu128
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-qwen2-7b") example_payloads = model.retrieve_al...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2-7b&smModelId=huggingface-llm-qwen2-7b&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen2-7B-Instruct
huggingface-llm-qwen2-7b-instruct
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi18.0.0-cu128
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-qwen2-7b-instruct") example_payloads = model.re...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2-7b-instruct&smModelId=huggingface-llm-qwen2-7b-instruct&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen2-VL-7B-Instruct
huggingface-vlm-qwen2-vl-7b-instruct
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi20.0.0-cu128
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model_id = "huggingface-vlm-qwen2-vl-7b-instruct" model = JumpStartModel(model_id=model_id) pay...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2-vl-7b-instruct&smModelId=huggingface-vlm-qwen2-vl-7b-instruct&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen2.5-14B-Instruct
huggingface-llm-qwen2-5-14b-instruct
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.6.0-tgi3.1.1-gpu-py311-cu124-ubuntu22.04
true
true
false
true
true
false
# Deploy a JumpStart model using the SageMaker Python SDK v3. from sagemaker.serve.model_builder import ModelBuilder from sagemaker.core.jumpstart.configs import JumpStartConfig from sagemaker.core.training.configs import Compute model_builder = ModelBuilder.from_jumpstart_config( jumpstart_config=JumpStartConfig...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-14b-instruct&smModelId=huggingface-llm-qwen2-5-14b-instruct&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-14b-instruct&smModelId=huggingface-llm-qwen2-5-14b-instruct&supportServerless=true&supportServerful=false&hasVariants=false&page=customize
# Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3. from sagemaker.train.dpo_trainer import DPOTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje...
Direct Preference Optimization (DPO)
[]
# Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3. from sagemaker.train.rlaif_trainer import RLAIFTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "...
RL from AI Feedback (RLAIF)
[]
# Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3. from sagemaker.train.rlvr_trainer import RLVRTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun...
RL with Verifiable Rewards (RLVR)
[]
# Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3. from sagemaker.train.sft_trainer import SFTTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line # Download ...
Supervised Fine-Tuning (SFT)
[]
Qwen/Qwen2.5-32B-Instruct
huggingface-llm-qwen2-5-32b-instruct
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.6.0-tgi3.1.1-gpu-py311-cu124-ubuntu22.04
true
true
false
true
true
false
# Deploy a JumpStart model using the SageMaker Python SDK v3. from sagemaker.serve.model_builder import ModelBuilder from sagemaker.core.jumpstart.configs import JumpStartConfig from sagemaker.core.training.configs import Compute model_builder = ModelBuilder.from_jumpstart_config( jumpstart_config=JumpStartConfig...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-32b-instruct&smModelId=huggingface-llm-qwen2-5-32b-instruct&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-32b-instruct&smModelId=huggingface-llm-qwen2-5-32b-instruct&supportServerless=true&supportServerful=false&hasVariants=false&page=customize
# Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3. from sagemaker.train.dpo_trainer import DPOTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje...
Direct Preference Optimization (DPO)
[]
# Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3. from sagemaker.train.rlaif_trainer import RLAIFTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "...
RL from AI Feedback (RLAIF)
[]
# Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3. from sagemaker.train.rlvr_trainer import RLVRTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun...
RL with Verifiable Rewards (RLVR)
[]
# Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3. from sagemaker.train.sft_trainer import SFTTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line # Download ...
Supervised Fine-Tuning (SFT)
[]
Qwen/Qwen2.5-72B-Instruct
huggingface-llm-qwen2-5-72b-instruct
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi22.0.0-cu129
false
true
false
true
true
false
# Deploy a JumpStart model using the SageMaker Python SDK v3. from sagemaker.serve.model_builder import ModelBuilder from sagemaker.core.jumpstart.configs import JumpStartConfig from sagemaker.core.training.configs import Compute model_builder = ModelBuilder.from_jumpstart_config( jumpstart_config=JumpStartConfig...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-72b-instruct&smModelId=huggingface-llm-qwen2-5-72b-instruct&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-72b-instruct&smModelId=huggingface-llm-qwen2-5-72b-instruct&supportServerless=true&supportServerful=false&hasVariants=false&page=customize
# Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3. from sagemaker.train.dpo_trainer import DPOTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje...
Direct Preference Optimization (DPO)
[]
# Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3. from sagemaker.train.rlaif_trainer import RLAIFTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "...
RL from AI Feedback (RLAIF)
[]
# Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3. from sagemaker.train.rlvr_trainer import RLVRTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun...
RL with Verifiable Rewards (RLVR)
[]
# Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3. from sagemaker.train.sft_trainer import SFTTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line # Download ...
Supervised Fine-Tuning (SFT)
[]
Qwen/Qwen2.5-7B-Instruct
huggingface-llm-qwen2-5-7b-instruct
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi22.0.0-cu129
false
true
false
true
true
false
# Deploy a JumpStart model using the SageMaker Python SDK v3. from sagemaker.serve.model_builder import ModelBuilder from sagemaker.core.jumpstart.configs import JumpStartConfig from sagemaker.core.training.configs import Compute model_builder = ModelBuilder.from_jumpstart_config( jumpstart_config=JumpStartConfig...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-7b-instruct&smModelId=huggingface-llm-qwen2-5-7b-instruct&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-7b-instruct&smModelId=huggingface-llm-qwen2-5-7b-instruct&supportServerless=true&supportServerful=false&hasVariants=false&page=customize
# Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3. from sagemaker.train.dpo_trainer import DPOTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje...
Direct Preference Optimization (DPO)
[]
# Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3. from sagemaker.train.rlaif_trainer import RLAIFTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "...
RL from AI Feedback (RLAIF)
[]
# Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3. from sagemaker.train.rlvr_trainer import RLVRTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun...
RL with Verifiable Rewards (RLVR)
[]
# Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3. from sagemaker.train.sft_trainer import SFTTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line # Download ...
Supervised Fine-Tuning (SFT)
[]
Qwen/Qwen2.5-Coder-32B-Instruct
huggingface-llm-qwen2-5-coder-32b-instruct
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.6.0-tgi3.2.3-gpu-py311-cu124-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-qwen2-5-coder-32b-instruct") example_payloads =...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-coder-32b-instruct&smModelId=huggingface-llm-qwen2-5-coder-32b-instruct&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen2.5-Coder-7B-Instruct
huggingface-llm-qwen2-5-coder-7b-instruct
763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-tgi-inference:2.6.0-tgi3.1.1-gpu-py311-cu124-ubuntu22.04
true
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-qwen2-5-coder-7b-instruct") example_payloads = ...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen2.5-coder-7b-instruct&smModelId=huggingface-llm-qwen2-5-coder-7b-instruct&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen3-0.6B
huggingface-reasoning-qwen3-06b
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi22.0.0-cu129
false
true
false
true
true
false
# Deploy a JumpStart model using the SageMaker Python SDK v3. from sagemaker.serve.model_builder import ModelBuilder from sagemaker.core.jumpstart.configs import JumpStartConfig from sagemaker.core.training.configs import Compute model_builder = ModelBuilder.from_jumpstart_config( jumpstart_config=JumpStartConfig...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-0.6b&smModelId=huggingface-reasoning-qwen3-06b&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-0.6b&smModelId=huggingface-reasoning-qwen3-06b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize
# Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3. from sagemaker.train.dpo_trainer import DPOTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje...
Direct Preference Optimization (DPO)
[]
# Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3. from sagemaker.train.rlaif_trainer import RLAIFTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "...
RL from AI Feedback (RLAIF)
[]
# Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3. from sagemaker.train.rlvr_trainer import RLVRTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun...
RL with Verifiable Rewards (RLVR)
[]
# Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3. from sagemaker.train.sft_trainer import SFTTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line # Download ...
Supervised Fine-Tuning (SFT)
[]
Qwen/Qwen3-1.7B
huggingface-reasoning-qwen3-1-7b
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi18.0.0-cu128
false
true
false
true
true
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-reasoning-qwen3-1-7b") example_payloads = model.ret...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-1.7b&smModelId=huggingface-reasoning-qwen3-1-7b&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-1.7b&smModelId=huggingface-reasoning-qwen3-1-7b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize
# Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3. from sagemaker.train.dpo_trainer import DPOTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje...
Direct Preference Optimization (DPO)
[]
# Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3. from sagemaker.train.rlaif_trainer import RLAIFTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "...
RL from AI Feedback (RLAIF)
[]
# Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3. from sagemaker.train.rlvr_trainer import RLVRTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun...
RL with Verifiable Rewards (RLVR)
[]
# Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3. from sagemaker.train.sft_trainer import SFTTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line # Download ...
Supervised Fine-Tuning (SFT)
[]
Qwen/Qwen3-14B
huggingface-reasoning-qwen3-14b
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi18.0.0-cu128
false
true
false
true
true
false
# Deploy a JumpStart model using the SageMaker Python SDK v3. from sagemaker.serve.model_builder import ModelBuilder from sagemaker.core.jumpstart.configs import JumpStartConfig from sagemaker.core.training.configs import Compute model_builder = ModelBuilder.from_jumpstart_config( jumpstart_config=JumpStartConfig...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-14b&smModelId=huggingface-reasoning-qwen3-14b&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-14b&smModelId=huggingface-reasoning-qwen3-14b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize
# Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3. from sagemaker.train.dpo_trainer import DPOTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje...
Direct Preference Optimization (DPO)
[]
# Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3. from sagemaker.train.rlaif_trainer import RLAIFTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "...
RL from AI Feedback (RLAIF)
[]
# Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3. from sagemaker.train.rlvr_trainer import RLVRTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun...
RL with Verifiable Rewards (RLVR)
[]
# Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3. from sagemaker.train.sft_trainer import SFTTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line # Download ...
Supervised Fine-Tuning (SFT)
[]
Qwen/Qwen3-30B-A3B
huggingface-reasoning-qwen3-30b-a3b
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi22.0.0-cu129
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-reasoning-qwen3-30b-a3b") example_payloads = model....
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-30b-a3b&smModelId=huggingface-reasoning-qwen3-30b-a3b&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen3-30B-A3B-Instruct-2507
huggingface-reasoning-qwen3-30b-a3b-instruct-2507
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi18.0.0-cu128
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-reasoning-qwen3-30b-a3b-instruct-2507") example_pay...
[{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-falcon.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/...
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-30b-a3b-instruct-2507&smModelId=huggingface-reasoning-qwen3-30b-a3b-instruct-2507&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen3-30B-A3B-Thinking-2507
huggingface-reasoning-qwen3-30b-a3b-thinking-2507
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi22.0.0-cu129
false
false
false
true
false
false
# Deploy a JumpStart model using the SageMaker Python SDK v3. from sagemaker.serve.model_builder import ModelBuilder from sagemaker.core.jumpstart.configs import JumpStartConfig from sagemaker.core.training.configs import Compute model_builder = ModelBuilder.from_jumpstart_config( jumpstart_config=JumpStartConfig...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-30b-a3b-thinking-2507&smModelId=huggingface-reasoning-qwen3-30b-a3b-thinking-2507&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen3-32B
huggingface-reasoning-qwen3-32b
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi20.0.0-cu128
false
true
false
true
true
false
# Deploy a JumpStart model using the SageMaker Python SDK v3. from sagemaker.serve.model_builder import ModelBuilder from sagemaker.core.jumpstart.configs import JumpStartConfig from sagemaker.core.training.configs import Compute model_builder = ModelBuilder.from_jumpstart_config( jumpstart_config=JumpStartConfig...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-32b&smModelId=huggingface-reasoning-qwen3-32b&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-32b&smModelId=huggingface-reasoning-qwen3-32b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize
# Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3. from sagemaker.train.dpo_trainer import DPOTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje...
Direct Preference Optimization (DPO)
[]
# Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3. from sagemaker.train.rlaif_trainer import RLAIFTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "...
RL from AI Feedback (RLAIF)
[]
# Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3. from sagemaker.train.rlvr_trainer import RLVRTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun...
RL with Verifiable Rewards (RLVR)
[]
# Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3. from sagemaker.train.sft_trainer import SFTTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line # Download ...
Supervised Fine-Tuning (SFT)
[]
Qwen/Qwen3-4B
huggingface-reasoning-qwen3-4b
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi18.0.0-cu128
false
true
false
true
true
false
# Deploy a JumpStart model using the SageMaker Python SDK v3. from sagemaker.serve.model_builder import ModelBuilder from sagemaker.core.jumpstart.configs import JumpStartConfig from sagemaker.core.training.configs import Compute model_builder = ModelBuilder.from_jumpstart_config( jumpstart_config=JumpStartConfig...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-4b&smModelId=huggingface-reasoning-qwen3-4b&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-4b&smModelId=huggingface-reasoning-qwen3-4b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize
# Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3. from sagemaker.train.dpo_trainer import DPOTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje...
Direct Preference Optimization (DPO)
[]
# Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3. from sagemaker.train.rlaif_trainer import RLAIFTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "...
RL from AI Feedback (RLAIF)
[]
# Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3. from sagemaker.train.rlvr_trainer import RLVRTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun...
RL with Verifiable Rewards (RLVR)
[]
# Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3. from sagemaker.train.sft_trainer import SFTTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line # Download ...
Supervised Fine-Tuning (SFT)
[]
Qwen/Qwen3-4B-Instruct-2507
huggingface-reasoning-qwen3-4b-instruct-2507
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi18.0.0-cu128
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-reasoning-qwen3-4b-instruct-2507") example_payloads...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-4b-instruct-2507&smModelId=huggingface-reasoning-qwen3-4b-instruct-2507&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen3-8B
huggingface-reasoning-qwen3-8b
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi22.0.0-cu129
false
true
false
true
true
false
# Deploy a JumpStart model using the SageMaker Python SDK v3. from sagemaker.serve.model_builder import ModelBuilder from sagemaker.core.jumpstart.configs import JumpStartConfig from sagemaker.core.training.configs import Compute model_builder = ModelBuilder.from_jumpstart_config( jumpstart_config=JumpStartConfig...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-8b&smModelId=huggingface-reasoning-qwen3-8b&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-8b&smModelId=huggingface-reasoning-qwen3-8b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize
# Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3. from sagemaker.train.dpo_trainer import DPOTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje...
Direct Preference Optimization (DPO)
[]
# Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3. from sagemaker.train.rlaif_trainer import RLAIFTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "...
RL from AI Feedback (RLAIF)
[]
# Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3. from sagemaker.train.rlvr_trainer import RLVRTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun...
RL with Verifiable Rewards (RLVR)
[]
# Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3. from sagemaker.train.sft_trainer import SFTTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line # Download ...
Supervised Fine-Tuning (SFT)
[]
Qwen/Qwen3-ASR-1.7B
huggingface-asr-qwen3-asr-1-7b
763104351884.dkr.ecr.us-east-2.amazonaws.com/vllm:server-sagemaker-cuda-v1
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-asr-qwen3-asr-1-7b") example_payloads = model.retri...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-asr-1.7b&smModelId=huggingface-asr-qwen3-asr-1-7b&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen3-Coder-30B-A3B-Instruct
huggingface-reasoning-qwen3-coder-30b-a3b-instruct
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi22.0.0-cu129
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-reasoning-qwen3-coder-30b-a3b-instruct") example_pa...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-coder-30b-a3b-instruct&smModelId=huggingface-reasoning-qwen3-coder-30b-a3b-instruct&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen3-Coder-Next
huggingface-reasoning-qwen3-coder-next
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi22.0.0-cu129
false
false
false
true
false
false
# Deploy a JumpStart model using the SageMaker Python SDK v3. from sagemaker.serve.model_builder import ModelBuilder from sagemaker.core.jumpstart.configs import JumpStartConfig from sagemaker.core.training.configs import Compute model_builder = ModelBuilder.from_jumpstart_config( jumpstart_config=JumpStartConfig...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-coder-next&smModelId=huggingface-reasoning-qwen3-coder-next&hasVariants=false&page=deploy
null
null
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null
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null
null
null
null
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null
Qwen/Qwen3-Embedding-0.6B
null
null
null
false
null
true
false
null
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-textembedding-qwen3-embedding-0-6b") example_payloa...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
null
null
null
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null
null
null
Qwen/Qwen3-Next-80B-A3B-Instruct
huggingface-reasoning-qwen3-next-80b-a3b-instruct
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.34.0-lmi16.0.0-cu128
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-reasoning-qwen3-next-80b-a3b-instruct") example_pay...
[{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-falcon.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/...
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-next-80b-a3b-instruct&smModelId=huggingface-reasoning-qwen3-next-80b-a3b-instruct&hasVariants=false&page=deploy
null
null
null
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null
null
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null
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null
null
Qwen/Qwen3-Reranker-4B
huggingface-textembedding-qwen3-reranker-4b
763104351884.dkr.ecr.us-east-2.amazonaws.com/vllm:0.19.1-gpu-py312-cu129-ubuntu22.04-sagemaker
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-textembedding-qwen3-reranker-4b") example_payloads ...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-reranker-4b&smModelId=huggingface-textembedding-qwen3-reranker-4b&hasVariants=false&page=deploy
null
null
null
null
null
null
null
null
null
null
null
null
null
Qwen/Qwen3-TTS-12Hz-1.7B-Base
huggingface-ttsvoiceclone-qwen3-tts-12hz-1-7b-base
763104351884.dkr.ecr.us-east-2.amazonaws.com/vllm:omni-sagemaker-cuda-v1.3.1
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-ttsvoiceclone-qwen3-tts-12hz-1-7b-base") example_pa...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-tts-12hz-1.7b-base&smModelId=huggingface-ttsvoiceclone-qwen3-tts-12hz-1-7b-base&hasVariants=false&page=deploy
null
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null
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null
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null
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Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice
null
null
null
false
null
true
false
null
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-tts-qwen3-tts-customvoice") example_payloads = mode...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
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null
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null
null
Qwen/Qwen3-VL-8B-Instruct
huggingface-vlm-qwen3-vl-8b-instruct
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi18.0.0-cu128
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model_id = "huggingface-vlm-qwen3-vl-8b-instruct" model = JumpStartModel(model_id=model_id) pay...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-vl-8b-instruct&smModelId=huggingface-vlm-qwen3-vl-8b-instruct&hasVariants=false&page=deploy
null
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Qwen/Qwen3-VL-Embedding-2B
huggingface-textembedding-qwen3-vl-embedding-2b
763104351884.dkr.ecr.us-east-2.amazonaws.com/vllm:0.19.1-gpu-py312-cu129-ubuntu22.04-sagemaker
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-textembedding-qwen3-vl-embedding-2b") example_paylo...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3-vl-embedding-2b&smModelId=huggingface-textembedding-qwen3-vl-embedding-2b&hasVariants=false&page=deploy
null
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Qwen/Qwen3.5-0.8B
huggingface-vlm-qwen3-5-0-8b
763104351884.dkr.ecr.us-east-2.amazonaws.com/vllm:0.19.1-gpu-py312-cu129-ubuntu22.04-sagemaker
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model_id = "huggingface-vlm-qwen3-5-0-8b" model = JumpStartModel(model_id=model_id) payload = m...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-0.8b&smModelId=huggingface-vlm-qwen3-5-0-8b&hasVariants=false&page=deploy
null
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Qwen/Qwen3.5-0.8B-Base
huggingface-vlm-qwen3-5-0-8b-base
763104351884.dkr.ecr.us-east-2.amazonaws.com/sglang:0.5.12-gpu-py312-cu130-ubuntu24.04-sagemaker-v1.2
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model_id = "huggingface-vlm-qwen3-5-0-8b-base" model = JumpStartModel(model_id=model_id) payloa...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-0.8b-base&smModelId=huggingface-vlm-qwen3-5-0-8b-base&hasVariants=false&page=deploy
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Qwen/Qwen3.5-122B-A10B
huggingface-llm-qwen3-5-122b-a10b
763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.36.0-lmi25.0.0-cu130
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id="huggingface-llm-qwen3-5-122b-a10b") example_payloads = model.re...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-122b-a10b&smModelId=huggingface-llm-qwen3-5-122b-a10b&hasVariants=false&page=deploy
null
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Qwen/Qwen3.5-27B
huggingface-vlm-qwen3-5-27b
763104351884.dkr.ecr.us-east-2.amazonaws.com/vllm:0.17-gpu-py312-cu129-ubuntu22.04-sagemaker-v1
false
true
false
true
true
false
# Deploy a JumpStart model using the SageMaker Python SDK v3. from sagemaker.serve.model_builder import ModelBuilder from sagemaker.core.jumpstart.configs import JumpStartConfig from sagemaker.core.training.configs import Compute model_builder = ModelBuilder.from_jumpstart_config( jumpstart_config=JumpStartConfig...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-27b&smModelId=huggingface-vlm-qwen3-5-27b&hasVariants=false&page=deploy
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-27b&smModelId=huggingface-vlm-qwen3-5-27b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize
# Fine-tune with Direct Preference Optimization (DPO) using the SageMaker Python SDK v3. from sagemaker.train.dpo_trainer import DPOTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "chosen": "...", "reje...
Direct Preference Optimization (DPO)
[]
# Fine-tune with RL from AI Feedback (RLAIF) using the SageMaker Python SDK v3. from sagemaker.train.rlaif_trainer import RLAIFTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"style": "...
RL from AI Feedback (RLAIF)
[]
# Fine-tune with RL with Verifiable Rewards (RLVR) using the SageMaker Python SDK v3. from sagemaker.train.rlvr_trainer import RLVRTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": [...messages...], "reward_model": {"groun...
RL with Verifiable Rewards (RLVR)
[]
# Fine-tune with Supervised Fine-Tuning (SFT) using the SageMaker Python SDK v3. from sagemaker.train.sft_trainer import SFTTrainer from sagemaker.train.common import TrainingType from sagemaker.ai_registry.dataset import DataSet # Dataset format: JSONL with {"prompt": "...", "completion": "..."} per line # Download ...
Supervised Fine-Tuning (SFT)
[]
Qwen/Qwen3.5-27B-FP8
huggingface-vlm-qwen3-5-27b-fp8
763104351884.dkr.ecr.us-east-2.amazonaws.com/vllm:0.17-gpu-py312-cu129-ubuntu22.04-sagemaker-v1
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model_id = "huggingface-vlm-qwen3-5-27b-fp8" model = JumpStartModel(model_id=model_id) payload ...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-27b-fp8&smModelId=huggingface-vlm-qwen3-5-27b-fp8&hasVariants=false&page=deploy
null
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Qwen/Qwen3.5-2B
huggingface-vlm-qwen3-5-2b
763104351884.dkr.ecr.us-east-2.amazonaws.com/vllm:0.19.1-gpu-py312-cu129-ubuntu22.04-sagemaker
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model_id = "huggingface-vlm-qwen3-5-2b" model = JumpStartModel(model_id=model_id) payload = mod...
[{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-2b&smModelId=huggingface-vlm-qwen3-5-2b&hasVariants=false&page=deploy
null
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Qwen/Qwen3.5-2B-Base
huggingface-vlm-qwen3-5-2b-base
763104351884.dkr.ecr.us-east-2.amazonaws.com/sglang:0.5.12-gpu-py312-cu130-ubuntu24.04-sagemaker-v1.2
false
false
false
true
false
false
# SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains. from sagemaker.jumpstart.model import JumpStartModel model_id = "huggingface-vlm-qwen3-5-2b-base" model = JumpStartModel(model_id=model_id) payload ...
[{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}]
null
null
https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=qwen%2Fqwen3.5-2b-base&smModelId=huggingface-vlm-qwen3-5-2b-base&hasVariants=false&page=deploy
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