Instructions to use HiTZ/Medical-mT5-large-multitask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HiTZ/Medical-mT5-large-multitask with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="HiTZ/Medical-mT5-large-multitask")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("HiTZ/Medical-mT5-large-multitask") model = AutoModelForSeq2SeqLM.from_pretrained("HiTZ/Medical-mT5-large-multitask", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use HiTZ/Medical-mT5-large-multitask with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "HiTZ/Medical-mT5-large-multitask" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "HiTZ/Medical-mT5-large-multitask", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/HiTZ/Medical-mT5-large-multitask
- SGLang
How to use HiTZ/Medical-mT5-large-multitask 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 "HiTZ/Medical-mT5-large-multitask" \ --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": "HiTZ/Medical-mT5-large-multitask", "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 "HiTZ/Medical-mT5-large-multitask" \ --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": "HiTZ/Medical-mT5-large-multitask", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use HiTZ/Medical-mT5-large-multitask with Docker Model Runner:
docker model run hf.co/HiTZ/Medical-mT5-large-multitask
| { | |
| "</Chemical>": 250117, | |
| "</Claim>": 250114, | |
| "</ClinicalEntity>": 250111, | |
| "</Dis>": 250112, | |
| "</Disease>": 250116, | |
| "</DiseaseNCBI>": 250115, | |
| "</NORMALIZABLES>": 250121, | |
| "</NO_NORMALIZABLES>": 250119, | |
| "</PROTEINAS>": 250118, | |
| "</Premise>": 250113, | |
| "</UNCLEAR>": 250120, | |
| "<Chemical>": 250106, | |
| "<Claim>": 250103, | |
| "<ClinicalEntity>": 250100, | |
| "<Dis>": 250101, | |
| "<Disease>": 250105, | |
| "<DiseaseNCBI>": 250104, | |
| "<NORMALIZABLES>": 250110, | |
| "<NO_NORMALIZABLES>": 250108, | |
| "<PROTEINAS>": 250107, | |
| "<Premise>": 250102, | |
| "<UNCLEAR>": 250109 | |
| } | |