Instructions to use badmatr11x/semantic-image-segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use badmatr11x/semantic-image-segmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="badmatr11x/semantic-image-segmentation")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("badmatr11x/semantic-image-segmentation") model = SegformerForSemanticSegmentation.from_pretrained("badmatr11x/semantic-image-segmentation") - 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 sha256:89e5289f21e9761bb890a30428d008c46f5ede605453da15c4b4c3c4b3d9633b
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size 338983704
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