Instructions to use TeeA/ViMATCHA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TeeA/ViMATCHA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="TeeA/ViMATCHA")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("TeeA/ViMATCHA") model = AutoModelForImageTextToText.from_pretrained("TeeA/ViMATCHA") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use TeeA/ViMATCHA with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TeeA/ViMATCHA" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TeeA/ViMATCHA", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TeeA/ViMATCHA
- SGLang
How to use TeeA/ViMATCHA 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 "TeeA/ViMATCHA" \ --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": "TeeA/ViMATCHA", "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 "TeeA/ViMATCHA" \ --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": "TeeA/ViMATCHA", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TeeA/ViMATCHA with Docker Model Runner:
docker model run hf.co/TeeA/ViMATCHA
- Xet hash:
- ba323a9ba2bac3d364fdf89c2ea266e8d90193ea2762ff9853ab67f771b92965
- Size of remote file:
- 5.05 kB
- SHA256:
- 105aa376ab38a199e85a8cd043d8586c43dd890393a9715442495a94e0c09987
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