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:
- 633d34fbd142211d3bd2ab393be7a10d68266ef26afad35af9003e2090a8b47c
- Size of remote file:
- 3.38 MB
- SHA256:
- bf74f6463e6d8308975ce91b34b44beb38cfc34b2d5183da2927ffaa6d538b52
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