Instructions to use adept/fuyu-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adept/fuyu-8b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="adept/fuyu-8b")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("adept/fuyu-8b") model = AutoModelForMultimodalLM.from_pretrained("adept/fuyu-8b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use adept/fuyu-8b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "adept/fuyu-8b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "adept/fuyu-8b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/adept/fuyu-8b
- SGLang
How to use adept/fuyu-8b 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 "adept/fuyu-8b" \ --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": "adept/fuyu-8b", "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 "adept/fuyu-8b" \ --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": "adept/fuyu-8b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use adept/fuyu-8b with Docker Model Runner:
docker model run hf.co/adept/fuyu-8b
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assert generation_text == ['A bus parked on the side of a road.']
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```
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Fuyu can also perform some question answering on natural images and charts/diagrams (thought fine-tuning may be required for good performance):
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```python
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text_prompt = "What color is the bus?\n"
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assert generation_text == ['A bus parked on the side of a road.']
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```
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N.B.: The token `|SPEAKER|` is a placeholder token for image patch embeddings, so it will show up in the model context (e.g., in the portion of `generation_output` representing the model context).
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`|NEWLINE|` is the "image newline" token, denoting new rows in the raster scan order input of the image patches.
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`\x04` is the "beginning of answer" token.
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Fuyu can also perform some question answering on natural images and charts/diagrams (thought fine-tuning may be required for good performance):
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```python
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text_prompt = "What color is the bus?\n"
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