Instructions to use basiliskan/slig with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use basiliskan/slig with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="basiliskan/slig") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("basiliskan/slig", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Create requirements.txt
Browse files- requirements.txt +7 -0
requirements.txt
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transformers>=4.45.0
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torch>=2.0.0
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Pillow>=10.0.0
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requests>=2.28.0
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accelerate>=0.26.0
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safetensors>=0.4.0
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sentencepiece>=0.1.99
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