Instructions to use rishitunu/ecc_segformerv5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rishitunu/ecc_segformerv5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("rishitunu/ecc_segformerv5") model = SegformerForSemanticSegmentation.from_pretrained("rishitunu/ecc_segformerv5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rishitunu/ecc_segformerv5: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/rishitunu/ecc_segformerv5/resolve/main/training_args.bin
- Command line
-
hf download hf://rishitunu/ecc_segformerv5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rishitunu/ecc_segformerv5/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 78e63af5310d3d0279e21bbf91dfe1e13a0a42ec71519ea9071755057a91fbc3
- Size of remote file:
- 4.03 kB
- SHA256:
- 5f1f6c2c743584ffa60d2224492f860105cca3388ea6af0b09e6fafc47e35318
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