Text Generation
Transformers
Safetensors
English
attn_ext
causal-lm
base-model
custom-code
research
custom_code
Instructions to use Bochkov/ab_ext_learned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bochkov/ab_ext_learned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Bochkov/ab_ext_learned", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Bochkov/ab_ext_learned", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Bochkov/ab_ext_learned with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Bochkov/ab_ext_learned" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Bochkov/ab_ext_learned", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Bochkov/ab_ext_learned
- SGLang
How to use Bochkov/ab_ext_learned with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Bochkov/ab_ext_learned" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Bochkov/ab_ext_learned", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Bochkov/ab_ext_learned" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Bochkov/ab_ext_learned", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Bochkov/ab_ext_learned with Docker Model Runner:
docker model run hf.co/Bochkov/ab_ext_learned
Download preprocessing_train_material.zip from Bochkov/ab_ext_learned: direct link, hf CLI and curl.
- Browser
- Download file 46.5 kB
-
https://huggingface.co/Bochkov/ab_ext_learned/resolve/main/preprocessing_train_material.zip
- Command line
-
hf download hf://Bochkov/ab_ext_learned/preprocessing_train_material.zip
-
curl -L -o preprocessing_train_material.zip https://huggingface.co/Bochkov/ab_ext_learned/resolve/main/preprocessing_train_material.zip
46.5 kB
- Xet hash:
- d382061cc08e9f2f539cb45b4e98c132f3f01f50b924a85ee015a1d2ef742470
- Size of remote file:
- 46.5 kB
- SHA256:
- 77dc5d8169ac3f55ff9b0cb490ec93947f74af2068a48dec5c01dcff0bb0543b
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