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")# Load model directly from transformers import AutoProcessor, CLIPSegForImageSegmentation processor = AutoProcessor.from_pretrained("CIDAS/clipseg-rd16") model = CLIPSegForImageSegmentation.from_pretrained("CIDAS/clipseg-rd16") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:51982c5ca4764643f0e29cfbf3313591b648d603a3fb4d0aaf159d38afb6e859
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size 599595736
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