Instructions to use sprx7767/chandassu-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sprx7767/chandassu-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sprx7767/chandassu-recognition")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sprx7767/chandassu-recognition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download notebook.ipynb from sprx7767/chandassu-recognition: direct link, hf CLI and curl.
- Browser
- Download file 5.97 kB
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https://huggingface.co/sprx7767/chandassu-recognition/resolve/main/notebook.ipynb
- Command line
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hf download hf://sprx7767/chandassu-recognition/notebook.ipynb
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curl -L -o notebook.ipynb https://huggingface.co/sprx7767/chandassu-recognition/resolve/main/notebook.ipynb
5.97 kB