Instructions to use hf-internal-testing/tiny-random-convnext with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-convnext with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-convnext") 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-convnext") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-convnext") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb79f62a8b46103537432baa2a40e7e6986592574753af6aa529d04cae3ac53f
- Size of remote file:
- 777 kB
- SHA256:
- 4ab875d514de01ba6ec469ee54521d3f4c2d0e457241cd7e8aaf92d049830dca
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