Instructions to use Fu-chiang/bit-50-IDRiD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fu-chiang/bit-50-IDRiD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Fu-chiang/bit-50-IDRiD") 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("Fu-chiang/bit-50-IDRiD") model = AutoModelForImageClassification.from_pretrained("Fu-chiang/bit-50-IDRiD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Fu-chiang/bit-50-IDRiD: direct link, hf CLI and curl.
- Browser
- Download file 188 MB
-
https://huggingface.co/Fu-chiang/bit-50-IDRiD/resolve/main/optimizer.pt
- Command line
-
hf download hf://Fu-chiang/bit-50-IDRiD/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Fu-chiang/bit-50-IDRiD/resolve/main/optimizer.pt
188 MB
- Xet hash:
- e68b94ef91c8b5074a1451215e6ae6165fa0eafe8e61d2fe7ea952c8461c7da0
- Size of remote file:
- 188 MB
- SHA256:
- fcfaa04e0287febdd52ab31d966ac470302c9ee058754b2b0525db98becf8e48
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