Instructions to use mcmonkey/clipseg-rd64-refined-fp16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mcmonkey/clipseg-rd64-refined-fp16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="mcmonkey/clipseg-rd64-refined-fp16")# Load model directly from transformers import AutoProcessor, CLIPSegForImageSegmentation processor = AutoProcessor.from_pretrained("mcmonkey/clipseg-rd64-refined-fp16") model = CLIPSegForImageSegmentation.from_pretrained("mcmonkey/clipseg-rd64-refined-fp16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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This is a copy of https://huggingface.co/CIDAS/clipseg-rd64-refined but as FP16 Safetensors, for use in Swarm https://github.com/Stability-AI/StableSwarmUI
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license: apache-2.0
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tags:
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- vision
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- image-segmentation
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inference: false
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This is a copy of https://huggingface.co/CIDAS/clipseg-rd64-refined but as FP16 Safetensors, for use in Swarm https://github.com/Stability-AI/StableSwarmUI
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