Instructions to use epfl-llm/meditron-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use epfl-llm/meditron-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="epfl-llm/meditron-7b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("epfl-llm/meditron-7b") model = AutoModelForCausalLM.from_pretrained("epfl-llm/meditron-7b") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use epfl-llm/meditron-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "epfl-llm/meditron-7b" # 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-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/epfl-llm/meditron-7b
- SGLang
How to use epfl-llm/meditron-7b 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-7b" \ --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-7b", "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-7b" \ --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-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use epfl-llm/meditron-7b with Docker Model Runner:
docker model run hf.co/epfl-llm/meditron-7b
Update README.md
#15 opened 3 months ago
by
manav1805
Tokenizer shape does not match model shape
β 1
#13 opened almost 2 years ago
by
lemousehunter
Llama-3-8B-Meditron v1.0
2
#12 opened about 2 years ago
by
djibe
[AUTOMATED] Model Memory Requirements
#11 opened about 2 years ago
by
model-sizer-bot
Can we use Meditron-7b for translation purpose?
2
#10 opened about 2 years ago
by
Hassan883
Is Meditron-7b better than LLaMA2-7b?
2
#9 opened about 2 years ago
by
sean0042
Detailed results on MMLU-Medical
1
#8 opened about 2 years ago
by
maximegmd
Repeated outputs in 7b as well as potential leakage/degenerate outputs.
π 1
5
#6 opened over 2 years ago
by
chonbas
CUDA error: device-side assert triggered
π 4
8
#5 opened over 2 years ago
by
bg90