Instructions to use hf-internal-testing/tiny-random-FlavaModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FlavaModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-FlavaModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-FlavaModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-FlavaModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 718f5531f119ae887974bfebcc43b9224b492b8911a4944f57a6f9f4c6f44cb5
- Size of remote file:
- 714 kB
- SHA256:
- 6e04e9a499b8d1588394a8ac76d3ff965468844b39e21f78a57030e4aeb528d7
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