Instructions to use nielsr/segformer-test-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nielsr/segformer-test-v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="nielsr/segformer-test-v5")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("nielsr/segformer-test-v5") model = SegformerForSemanticSegmentation.from_pretrained("nielsr/segformer-test-v5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3fb1d5102a3bf1d7541ecbd988e9d261904b229086dcbdb1242412c4f6dfe213
- Size of remote file:
- 29.9 MB
- SHA256:
- 8e33fc945bb964f8e27fb7485094b6694e146441a604f307a02d8086d5fdb0f9
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