Instructions to use CIDAS/clipseg-rd16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CIDAS/clipseg-rd16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="CIDAS/clipseg-rd16")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, CLIPSegForImageSegmentation processor = AutoProcessor.from_pretrained("CIDAS/clipseg-rd16") model = CLIPSegForImageSegmentation.from_pretrained("CIDAS/clipseg-rd16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#2)
Verified signature- Adding `safetensors` variant of this model (a4d02d29b45c0ee3d40ad6003d79c8c5884540b3) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>25c8f28
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Update preprocessor_config.json
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Create README.md
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Upload processor
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Upload CLIPSegForImageSegmentation
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Upload processor
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Upload CLIPSegForImageSegmentation
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initial commit
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