Instructions to use hf-tiny-model-private/tiny-random-XCLIPModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-XCLIPModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-XCLIPModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-XCLIPModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-XCLIPModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0fe23dcefb4fdd43ab2975ccbf5132f844850b0a5748920147446b15e39d80b0
- Size of remote file:
- 2.26 MB
- SHA256:
- e1a8e961c9b2044219dfe1ee37e1cbcdca7044f0b0966c4df0403bff8e23fbfc
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