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:
- f247a89c7b5aa1bef5e92aba9447632795b4229f0af5f578fd37c09d76d27978
- Size of remote file:
- 3.11 MB
- SHA256:
- 319db9f24233984f030259cd71ffc430f9f5567805dcffc9c343ba991fe8c587
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