Text Generation
Transformers
PyTorch
Safetensors
English
llama
medical
health
llama2
text-generation-inference
Instructions to use epfl-llm/meditron-70b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use epfl-llm/meditron-70b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="epfl-llm/meditron-70b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("epfl-llm/meditron-70b") model = AutoModelForCausalLM.from_pretrained("epfl-llm/meditron-70b") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use epfl-llm/meditron-70b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "epfl-llm/meditron-70b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "epfl-llm/meditron-70b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/epfl-llm/meditron-70b
- SGLang
How to use epfl-llm/meditron-70b 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 "epfl-llm/meditron-70b" \ --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": "epfl-llm/meditron-70b", "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 "epfl-llm/meditron-70b" \ --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": "epfl-llm/meditron-70b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use epfl-llm/meditron-70b with Docker Model Runner:
docker model run hf.co/epfl-llm/meditron-70b
Remove access
#15 opened 6 months ago
by
jimmcgaw
The Development Concept of This Model is So Cool
π 1
#14 opened over 1 year ago
by
qingyuanc
Inquiry on MEDITRON LLaMA 3 Version Release
π 1
#13 opened almost 2 years ago
by
Nagafi
This is so cool + Llama3
πβ€οΈ 4
4
#11 opened about 2 years ago
by
clem
Getting an issue with Cuda
ππ₯ 1
3
#10 opened about 2 years ago
by
LLMHackathonNYC
Update model.safetensors.index.json
#9 opened over 2 years ago
by
Alburrito18
Using Axolotl for Fine Tuning
#7 opened over 2 years ago
by
zero1zero
when attempting to download/save model to run on replicate.com I get KeyError: 'llama'
#6 opened over 2 years ago
by
ghthaker1955
How to run/access this model using API calls on either "inference endpoints", "replicate" or own 64Gb Linux desktop?
1
#5 opened over 2 years ago
by
ghthaker1955
The config.json does not seem to match the new instruction finetuning.
π 1
3
#4 opened over 2 years ago
by
paulhager