Instructions to use hf-tiny-model-private/tiny-random-Data2VecVisionForSemanticSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-Data2VecVisionForSemanticSegmentation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, Data2VecVisionForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecVisionForSemanticSegmentation") model = Data2VecVisionForSemanticSegmentation.from_pretrained("hf-tiny-model-private/tiny-random-Data2VecVisionForSemanticSegmentation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from hf-tiny-model-private/tiny-random-Data2VecVisionForSemanticSegmentation: direct link, hf CLI and curl.
- Browser
- Download file 1.14 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-Data2VecVisionForSemanticSegmentation/resolve/main/tf_model.h5
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-Data2VecVisionForSemanticSegmentation/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/hf-tiny-model-private/tiny-random-Data2VecVisionForSemanticSegmentation/resolve/main/tf_model.h5
1.14 MB
- Xet hash:
- 53e14ccd2d2efd20ac0e6ea7ca405bfe454ac34604e2531bd4113769dfc7ffa3
- Size of remote file:
- 1.14 MB
- SHA256:
- c5fe1a9a410acba298bbda3ee06a8ae2a15a96f9abfe2c2888089bbeee8447fd
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