Instructions to use HuggingFaceM4/idefics-9b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use HuggingFaceM4/idefics-9b with Transformers:

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

pipe = pipeline("text-generation", model="HuggingFaceM4/idefics-9b")

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("HuggingFaceM4/idefics-9b")
model = AutoModelForImageTextToText.from_pretrained("HuggingFaceM4/idefics-9b")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use HuggingFaceM4/idefics-9b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "HuggingFaceM4/idefics-9b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HuggingFaceM4/idefics-9b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/HuggingFaceM4/idefics-9b

SGLang

How to use HuggingFaceM4/idefics-9b 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 "HuggingFaceM4/idefics-9b" \
    --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": "HuggingFaceM4/idefics-9b",
		"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 "HuggingFaceM4/idefics-9b" \
        --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": "HuggingFaceM4/idefics-9b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use HuggingFaceM4/idefics-9b with Docker Model Runner:
```
docker model run hf.co/HuggingFaceM4/idefics-9b
```

idefics-9b

Commit History

processor config

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stas commited on Jul 19, 2023

Revert "processor config"

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processor config

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rename

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add missing metadata

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Update README.md

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stas commited on Jul 11, 2023

add tokenizer

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stas commited on Jul 11, 2023

add checkpoints

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stas commited on Jul 11, 2023

initial commit

4ffa24d

Stas Bekman commited on Jul 11, 2023

Commit History

processor config 3b8ef03

Revert "processor config" 5df3a85

processor config 2c22c33

rename 1c0bf47

add missing metadata 280387a

Update README.md cd2f5b8

add tokenizer bdf12f5

add checkpoints 32935e1

initial commit 4ffa24d

processor config

3b8ef03

Revert "processor config"

5df3a85

processor config

2c22c33

rename

1c0bf47

add missing metadata

280387a

Update README.md

cd2f5b8

add tokenizer

bdf12f5

add checkpoints

32935e1

initial commit

4ffa24d