Instructions to use ILT37/Image-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ILT37/Image-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ILT37/Image-classification") 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("ILT37/Image-classification") model = AutoModelForImageClassification.from_pretrained("ILT37/Image-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from ILT37/Image-classification: direct link, hf CLI and curl.
- Browser
- Download file 344 MB
-
https://huggingface.co/ILT37/Image-classification/resolve/main/model.safetensors
- Command line
-
hf download hf://ILT37/Image-classification/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ILT37/Image-classification/resolve/main/model.safetensors
344 MB
- Xet hash:
- 43dd09be6154221196a9e41ec96e475f42e79c9b260f24a5f1001311bf9d4fef
- Size of remote file:
- 344 MB
- SHA256:
- de097412cad8746b6eb19ea1dc0e2199ef3d2a9a8accae460a9a51bf4e2f8331
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