Image Classification
Transformers
Safetensors
English
siglip
fashion
product
season
siglip2
image
classification
Instructions to use prithivMLmods/Fashion-Product-Season with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Fashion-Product-Season with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Fashion-Product-Season") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Fashion-Product-Season") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Fashion-Product-Season", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from prithivMLmods/Fashion-Product-Season: direct link, hf CLI and curl.
- Browser
- Download file 372 MB
-
https://huggingface.co/prithivMLmods/Fashion-Product-Season/resolve/main/model.safetensors
- Command line
-
hf download hf://prithivMLmods/Fashion-Product-Season/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/prithivMLmods/Fashion-Product-Season/resolve/main/model.safetensors
372 MB
- Xet hash:
- 07a0b73f0023641fb2f2ce9583a6e48f2bfe4b5f2de455ca1f1d3bf619afb68a
- Size of remote file:
- 372 MB
- SHA256:
- b9d36e8e7b1fa970a6d3d42382bd392470b39f99bea801ed1c0f9ba7259ce8da
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