Instructions to use hf-tiny-model-private/tiny-random-FlavaModel 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-FlavaModel 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-FlavaModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-FlavaModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-FlavaModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c076a81ad92f458f1a80420090d32ab1c224b1a658478794e20682ebea02b17e
- Size of remote file:
- 773 kB
- SHA256:
- 99e39df54bd2974bfcecb4804ad552b51eccbf7e5af8a28152db45d890f3b784
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