Instructions to use hf-internal-testing/tiny-random-PvtV2ForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PvtV2ForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-PvtV2ForImageClassification") 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-PvtV2ForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-PvtV2ForImageClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f796c7c795d6e18542fb3dd0798e7594605c8383929e2019168827160a7667e
- Size of remote file:
- 3.11 MB
- SHA256:
- 52e868f7b9b4f385e156bbca95caf9fe83d2633aea03eae4484b18e73408fb43
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