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 AutoProcessor, AutoModel processor = AutoProcessor.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:
- 3964204003384731599022d965ed2f710996b1bbe2ba1eb2d56b15fa452f8086
- Size of remote file:
- 2.2 MB
- SHA256:
- ee5d38e8bd168eab907ab1ed98d387c2df5cb4b01865b30a73892e8e7b64fc85
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