Instructions to use hf-internal-testing/tiny-random-XCLIPModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XCLIPModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-XCLIPModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-XCLIPModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-XCLIPModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63a9c43b14f35593a2a6d6e682d620ccb5a2da6089b20d6a91a98a8b7a022993
- Size of remote file:
- 2.2 MB
- SHA256:
- 27d7cc9c80deb0a3af30c2883f56213861ba036ea0eaeedb0f55e82a3656183d
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