Instructions to use parhamjanjan87/Tomur-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use parhamjanjan87/Tomur-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="parhamjanjan87/Tomur-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("parhamjanjan87/Tomur-Classification") model = AutoModelForImageClassification.from_pretrained("parhamjanjan87/Tomur-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from parhamjanjan87/Tomur-Classification: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/parhamjanjan87/Tomur-Classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://parhamjanjan87/Tomur-Classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/parhamjanjan87/Tomur-Classification/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 17a74f725439ac1e229a30a97871e12ab51284c18e4f429cd4c57b8b7f07fcf3
- Size of remote file:
- 343 MB
- SHA256:
- 37da631c46f6a82e4a4b823b9e381564eb4e449b6145fd413f23d3bb59c6b1ce
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