Instructions to use hf-internal-testing/tiny-random-Blip2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Blip2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-Blip2Model")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Blip2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-Blip2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0926400a8f0704895fba90799db407df48e887650fe981ef1469458765e6bf58
- Size of remote file:
- 899 kB
- SHA256:
- e2acc6e27884449b4f057e91bfd73d03643e6f0fe3d248913a0f64d742b68846
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