Instructions to use Isaacks/test_push with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Isaacks/test_push with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="Isaacks/test_push")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("Isaacks/test_push") model = SegformerForSemanticSegmentation.from_pretrained("Isaacks/test_push", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_state.pth from Isaacks/test_push: direct link, hf CLI and curl.
- Browser
- Download file 14.9 MB
-
https://huggingface.co/Isaacks/test_push/resolve/main/model_state.pth
- Command line
-
hf download hf://Isaacks/test_push/model_state.pth
-
curl -L -o model_state.pth https://huggingface.co/Isaacks/test_push/resolve/main/model_state.pth
14.9 MB
- Xet hash:
- 05fa27e90fa2f1f1382102d0e261bd389c575753af767363278af2ef67d163f9
- Size of remote file:
- 14.9 MB
- SHA256:
- 6e21ce64823453c771bc1d899ebc74ae30a68f20292a7e00b60e7a9921b837db
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