Instructions to use Transformers123/testing_303 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Transformers123/testing_303 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="Transformers123/testing_303")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("Transformers123/testing_303") model = SegformerForSemanticSegmentation.from_pretrained("Transformers123/testing_303", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Transformers123/testing_303: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/Transformers123/testing_303/resolve/main/training_args.bin
- Command line
-
hf download hf://Transformers123/testing_303/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Transformers123/testing_303/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 0f405916979f855b34cedda52f9593fc6d54fe4183927e5eb880a73e0c27a49a
- Size of remote file:
- 4.09 kB
- SHA256:
- 735175cecc8cd72d8d5c1d8a36b8a8b15145f51be4b2d6142a38b3f6f489af34
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