Instructions to use zer0int/CLIP-SAE-ViT-L-14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zer0int/CLIP-SAE-ViT-L-14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="zer0int/CLIP-SAE-ViT-L-14") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("zer0int/CLIP-SAE-ViT-L-14") model = AutoModelForZeroShotImageClassification.from_pretrained("zer0int/CLIP-SAE-ViT-L-14") - Notebooks
- Google Colab
- Kaggle
'import clip' original OpenAI format torch.save
Browse filesOriginal pickle files as saved from the fine-tuning script.
ViT-L-14-GmP-SAE-pickle-OpenAI.pt
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oid sha256:bb8394976e64f543d48eefe95c0ab180b7b7ad217444f85d5baece6e0e7bc829
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ViT-L-14-GmP-SAE-state_dict.pt
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oid sha256:d78e8fff17f0bf3716435e77b5ea02241b4c74022ccf9b6887caf01ea922522a
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size 1710649272
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