Instructions to use dataguychill/VioMobileNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use dataguychill/VioMobileNet with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("dataguychill/VioMobileNet") - Notebooks
- Google Colab
- Kaggle
Download Dockerfile from dataguychill/VioMobileNet: direct link, hf CLI and curl.
- Browser
- Download file 444 Bytes
-
https://huggingface.co/dataguychill/VioMobileNet/resolve/main/Dockerfile
- Command line
-
hf download hf://dataguychill/VioMobileNet/Dockerfile
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curl -L -o Dockerfile https://huggingface.co/dataguychill/VioMobileNet/resolve/main/Dockerfile
444 Bytes
| FROM tensorflow/tensorflow:2.15.0-gpu | |
| RUN apt-get update && apt-get install -y libgl1-mesa-glx libglib2.0-0 && rm -rf /var/lib/apt/lists/* | |
| WORKDIR /app | |
| # Copy code | |
| COPY . . | |
| # Install dependencies | |
| RUN pip install "numpy<2" opencv-python fastapi uvicorn[standard] websockets | |
| ENV MODEL_PATH="model" | |
| ENV RESOLUTION="172" | |
| # Mở port 8000 | |
| EXPOSE 8000 | |
| # Chạy Server FastAPI | |
| CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"] | |