Instructions to use gitfreder/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gitfreder/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gitfreder/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("gitfreder/image_classification") model = AutoModelForImageClassification.from_pretrained("gitfreder/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from gitfreder/image_classification: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/gitfreder/image_classification/resolve/main/model.safetensors
- Command line
-
hf download hf://gitfreder/image_classification/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/gitfreder/image_classification/resolve/main/model.safetensors
343 MB
- Xet hash:
- 9cc415dea229ddead73c8c3c6dc17d104d965b59690022d7887ddf299651cb7a
- Size of remote file:
- 343 MB
- SHA256:
- bfcf1c600654078c831a7be8679d00a650213f071346f128f0f9515f9e9fe32f
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