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:
- 72282d753ed97cb99643e74da4f132ff74ce7aacf1115283c4d592f7e553834f
- Size of remote file:
- 907 kB
- SHA256:
- fb096ca18d04b1aa415e6bc5952d986fc01928573aa3160bb6851931a65f230b
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