Instructions to use hf-internal-testing/tiny-random-PvtForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PvtForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-PvtForImageClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-PvtForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-PvtForImageClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46d39c48a7d101b9a87b3d430c96b981db24dce2769d7dc113adfbb5e756d149
- Size of remote file:
- 3.38 MB
- SHA256:
- be52e9625a625626876ed118562d7e3361d5d194a7ee9fd7b544aae33229a71b
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