Instructions to use microsoft/llava-med-7b-delta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use microsoft/llava-med-7b-delta with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="microsoft/llava-med-7b-delta")

# Load model directly
from transformers import AutoProcessor, AutoModelForCausalLM

processor = AutoProcessor.from_pretrained("microsoft/llava-med-7b-delta")
model = AutoModelForCausalLM.from_pretrained("microsoft/llava-med-7b-delta")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use microsoft/llava-med-7b-delta with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "microsoft/llava-med-7b-delta"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "microsoft/llava-med-7b-delta",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/microsoft/llava-med-7b-delta

SGLang

How to use microsoft/llava-med-7b-delta 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 "microsoft/llava-med-7b-delta" \
    --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": "microsoft/llava-med-7b-delta",
		"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 "microsoft/llava-med-7b-delta" \
        --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": "microsoft/llava-med-7b-delta",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use microsoft/llava-med-7b-delta with Docker Model Runner:
```
docker model run hf.co/microsoft/llava-med-7b-delta
```

Update base model checkpoint files to new version

by katielink - opened Nov 16, 2023

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

-1

katielink

Nov 16, 2023

The checkpoints were recently updated by the Microsoft team on their Github repo. These new checkpoints represent the base model for the finetuned versions (also being uploaded in separate repos).

Update base model checkpoint files to new versionc2e341ef

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