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, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("adept/fuyu-8b") model = AutoModelForImageTextToText.from_pretrained("adept/fuyu-8b") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- 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
Support multi-image?
Thanks for your great work! Does fuyu-8b support multi-image as input?
It does but the processor does not at the moment, a PR is on it's way for this!
Thank you for the great work! Regarding the ability to support multi-image, does it mean that fuyu-8b can handle interleaved text and multi-images? Could you clarify the input format for the transformer decoder when there is interleaved text and multi-images?
From the blog, it appears that the input for a single image and text would be: [img_patch] [img_patch] \n [img_patch] [img_patch] \n [text].
How would the format change in the scenario where the sequence is "<img1> <img2> some text"? Would there be some special image token to separate the two images? Or it would be like [img1_patch] [img1_patch] \n [img1_patch] [img1_patch] \n [img2_patch] [img2_patch] \n [img2_patch] [img2_patch] \n [text]?
Also, does FuyuForCausalLM need any modification in order to accommodate interleaved text and multi-images? Thank you!
I think it does support interleaved images, I'm not entirely sure how two images are prompted, we'll try to ask the authors!
Any update on supporting interleaved images?