Instructions to use hf-internal-testing/tiny-random-Blip2ForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Blip2ForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="hf-internal-testing/tiny-random-Blip2ForConditionalGeneration")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Blip2ForConditionalGeneration") model = AutoModelForVisualQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-Blip2ForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e64aa55849e4730465b0885db95d6690475504523f5276f2bc1be1abf3fc917
- Size of remote file:
- 965 kB
- SHA256:
- c82e25ae129cbe44b4fabcbefee62d6bcc15e0d91df135f3ec2137c63ad6383a
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