Instructions to use hf-internal-testing/tiny-random-CLIPForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-CLIPForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-CLIPForImageClassification") 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("hf-internal-testing/tiny-random-CLIPForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-CLIPForImageClassification") - Notebooks
- Google Colab
- Kaggle
Update tiny models for CLIPForImageClassification
#10 opened about 2 years ago
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Update tiny models for CLIPForImageClassification
#9 opened over 2 years ago
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Update tiny models for CLIPForImageClassification
#8 opened over 2 years ago
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Update tiny models for CLIPForImageClassification
#7 opened over 2 years ago
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Update tiny models for CLIPForImageClassification
#6 opened over 2 years ago
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Update tiny models for CLIPForImageClassification
#5 opened over 2 years ago
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Update tiny models for CLIPForImageClassification
#4 opened over 2 years ago
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Update tiny models for CLIPForImageClassification
#3 opened over 2 years ago
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Update tiny models for CLIPForImageClassification
#2 opened over 2 years ago
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hf-transformers-bot
Update tiny models for CLIPForImageClassification
#1 opened over 2 years ago
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hf-transformers-bot