Instructions to use prithivMLmods/Brain3-Anomaly-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Brain3-Anomaly-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Brain3-Anomaly-SigLIP2") 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/Brain3-Anomaly-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Brain3-Anomaly-SigLIP2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ddd7d6191ef14ea0d4ae79e5f57bfd5ec6b76899d332f01c0c640a9bf9b36b6d
- Size of remote file:
- 687 MB
- SHA256:
- 2effe7c53b6ea1a93f73442b034e03a8c02c465a5e39f3e2a55ca4a80c858209
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