Instructions to use nathanReitinger/FASHION-vision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nathanReitinger/FASHION-vision with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nathanReitinger/FASHION-vision") 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("nathanReitinger/FASHION-vision") model = AutoModelForImageClassification.from_pretrained("nathanReitinger/FASHION-vision", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from nathanReitinger/FASHION-vision: direct link, hf CLI and curl.
- Browser
- Download file 5.05 GB
-
https://huggingface.co/nathanReitinger/FASHION-vision/resolve/main/optimizer.pt
- Command line
-
hf download hf://nathanReitinger/FASHION-vision/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/nathanReitinger/FASHION-vision/resolve/main/optimizer.pt
5.05 GB
- Xet hash:
- eadb33a44f8b45caa650bb96c91a64dc36f69fb164fa71c14da024571413e33f
- Size of remote file:
- 5.05 GB
- SHA256:
- 1b42b5ec4ddd184cde90ff444ee826a7986acf3f915b90f74b1c6a33a4eae4df
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