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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 48f3a4c02246bf6e60ebb53d9fb5292d4efa7e39940311c6faf31fb9f629387d
- Size of remote file:
- 418 kB
- SHA256:
- eeb9ce52e648d4057aaa03fc6de3435347a3efb4b6bb6be1ba3c17923acc6fd5
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