Instructions to use hf-tiny-model-private/tiny-random-Blip2Model 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-Blip2Model 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-Blip2Model")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-Blip2Model") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-Blip2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cce5a1a66a99c6260db71e410b125637c241946cad68563bb42d4551182ef92e
- Size of remote file:
- 899 kB
- SHA256:
- 75e973a97b439fe3f7d5e1607b4ca73c0d226e7594bddb46bfcff65e75cbad80
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