Instructions to use gaganpathre/amgerindaf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gaganpathre/amgerindaf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gaganpathre/amgerindaf") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("gaganpathre/amgerindaf") model = AutoModelForImageClassification.from_pretrained("gaganpathre/amgerindaf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gaganpathre/amgerindaf: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/gaganpathre/amgerindaf/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gaganpathre/amgerindaf/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gaganpathre/amgerindaf/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- bc2c452824008df202eb08a7ea7b0b81397b826a070afbd8b6deb38dfd73c126
- Size of remote file:
- 343 MB
- SHA256:
- d5f713ff87675a00caea5a3ab486458b57c54e8a69c0a02f80288869592cf6df
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