Instructions to use kanashi6/UFO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kanashi6/UFO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="kanashi6/UFO")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kanashi6/UFO", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use kanashi6/UFO with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "kanashi6/UFO" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kanashi6/UFO", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/kanashi6/UFO
- SGLang
How to use kanashi6/UFO 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 "kanashi6/UFO" \ --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": "kanashi6/UFO", "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 "kanashi6/UFO" \ --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": "kanashi6/UFO", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use kanashi6/UFO with Docker Model Runner:
docker model run hf.co/kanashi6/UFO
Add/improve model card
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license: apache-2.0
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license: apache-2.0
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library_name: transformers
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pipeline_tag: image-to-image
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---
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This repository contains the model presented in the paper [UFO: A Unified Approach to Fine-grained Visual Perception via Open-ended Language Interface](https://hf.co/papers/2503.01342).
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UFO unifies object-level detection, pixel-level segmentation, and image-level vision-language tasks into a single model by transforming all perception targets into the language space. It introduces a novel embedding retrieval approach that relies solely on the language interface to support segmentation tasks.
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For more details, please refer to the original paper and the GitHub repository:
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- Paper: [UFO: A Unified Approach to Fine-grained Visual Perception via Open-ended Language Interface](https://hf.co/papers/2503.01342)
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- GitHub: [https://github.com/nnnth/UFO](https://github.com/nnnth/UFO)
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