Instructions to use hf-internal-testing/tiny-random-BlipForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BlipForQuestionAnswering 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-BlipForQuestionAnswering")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-BlipForQuestionAnswering") model = AutoModelForVisualQuestionAnswering.from_pretrained("hf-internal-testing/tiny-random-BlipForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8618422063c0a543580b833d979a17c0b320ad2cc33a3a2b8367ef5d2681425f
- Size of remote file:
- 852 kB
- SHA256:
- cc01c4d85713e0222cd32d75b6f2cca956746e5c9bcb3071b94e8709b466e113
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