Instructions to use hf-internal-testing/tiny-random-ConvNextModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ConvNextModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-ConvNextModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ConvNextModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ConvNextModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5abceb5e4cf0be45aeee4b58ff54fef882dd89e6be272482004c80e9e7899122
- Size of remote file:
- 338 kB
- SHA256:
- fe5b90669ff950489029d4f5a02fcb03f8b7f886aadd7762e691145b59eb218f
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