Instructions to use hf-tiny-model-private/tiny-random-MBartForCausalLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MBartForCausalLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="hf-tiny-model-private/tiny-random-MBartForCausalLM")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-MBartForCausalLM") model = AutoModelForCausalLM.from_pretrained("hf-tiny-model-private/tiny-random-MBartForCausalLM") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use hf-tiny-model-private/tiny-random-MBartForCausalLM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hf-tiny-model-private/tiny-random-MBartForCausalLM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hf-tiny-model-private/tiny-random-MBartForCausalLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/hf-tiny-model-private/tiny-random-MBartForCausalLM
- SGLang
How to use hf-tiny-model-private/tiny-random-MBartForCausalLM 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 "hf-tiny-model-private/tiny-random-MBartForCausalLM" \ --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": "hf-tiny-model-private/tiny-random-MBartForCausalLM", "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 "hf-tiny-model-private/tiny-random-MBartForCausalLM" \ --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": "hf-tiny-model-private/tiny-random-MBartForCausalLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use hf-tiny-model-private/tiny-random-MBartForCausalLM with Docker Model Runner:
docker model run hf.co/hf-tiny-model-private/tiny-random-MBartForCausalLM
| { | |
| "additional_special_tokens": [ | |
| "ar_AR", | |
| "cs_CZ", | |
| "de_DE", | |
| "en_XX", | |
| "es_XX", | |
| "et_EE", | |
| "fi_FI", | |
| "fr_XX", | |
| "gu_IN", | |
| "hi_IN", | |
| "it_IT", | |
| "ja_XX", | |
| "kk_KZ", | |
| "ko_KR", | |
| "lt_LT", | |
| "lv_LV", | |
| "my_MM", | |
| "ne_NP", | |
| "nl_XX", | |
| "ro_RO", | |
| "ru_RU", | |
| "si_LK", | |
| "tr_TR", | |
| "vi_VN", | |
| "zh_CN" | |
| ], | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "mask_token": { | |
| "content": "<mask>", | |
| "lstrip": true, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "unk_token": "<unk>" | |
| } | |