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
File size: 68 Bytes
d0de11f | 1 2 3 4 5 | {
"num_query_tokens": 10,
"processor_class": "Blip2Processor"
}
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