Instructions to use mattmdjaga/segformer_b0_clothes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mattmdjaga/segformer_b0_clothes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="mattmdjaga/segformer_b0_clothes")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("mattmdjaga/segformer_b0_clothes") model = SegformerForSemanticSegmentation.from_pretrained("mattmdjaga/segformer_b0_clothes") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c5e899f934791161f3a115b39c8ce595d17e165904100c23e2b5e76fb0a3f46
- Size of remote file:
- 14.9 MB
- SHA256:
- 15a0c8b7a114c2577ad1ba3be90e357021dec432687f8a360df1b515c11e4497
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