Instructions to use ph0masta/bug_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ph0masta/bug_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ph0masta/bug_classifier") 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("ph0masta/bug_classifier") model = AutoModelForImageClassification.from_pretrained("ph0masta/bug_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ph0masta/bug_classifier: direct link, hf CLI and curl.
- Browser
- Download file 344 MB
-
https://huggingface.co/ph0masta/bug_classifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ph0masta/bug_classifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ph0masta/bug_classifier/resolve/main/pytorch_model.bin
344 MB
- Xet hash:
- b2568264a585149c0266914980a3b057397de095a1aba73613abd36e66c28bc6
- Size of remote file:
- 344 MB
- SHA256:
- 31c58930cf904f36bddf3a726f4d4ebd545c8bfd6f5d22fa5b684b6f44d83135
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