Instructions to use Baicai003/tiny-clip-one with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Baicai003/tiny-clip-one with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Baicai003/tiny-clip-one")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Baicai003/tiny-clip-one") model = AutoModel.from_pretrained("Baicai003/tiny-clip-one", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38ed9a372f4ce682d984bbb9620eb494bb5a04c83bc8314bf1b55e4a92867297
- Size of remote file:
- 4.24 MB
- SHA256:
- 57241fb8259385cfb669133424908209f39dac7d59b77f2ccb9169b4dd0f8feb
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