Instructions to use hf-internal-testing/tiny-random-PvtModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PvtModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-PvtModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-PvtModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-PvtModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 671672dcc42e8df7a81c0b7dddf91487a807992f7c4b0eef15a2c024d949b4f3
- Size of remote file:
- 2.86 MB
- SHA256:
- 76e2f99c7cbf98a99b9a7ace2b2778b0aa12b6c848ff5aa42229620fedfcf1d0
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