Image-to-Text
Transformers
PyTorch
Safetensors
English
blip-2
visual-question-answering
vision
image-captioning
Instructions to use Salesforce/blip2-flan-t5-xl-coco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Salesforce/blip2-flan-t5-xl-coco with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="Salesforce/blip2-flan-t5-xl-coco")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("Salesforce/blip2-flan-t5-xl-coco") model = AutoModelForVisualQuestionAnswering.from_pretrained("Salesforce/blip2-flan-t5-xl-coco") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e8ea6a0d7c60eabebaa4b42e5fceeb0e854b407ffdf0b671a6d6451225b40f1a
- Size of remote file:
- 9.44 GB
- SHA256:
- 2a91a6c44a9cc9c814b244306a341c822dd9ce426b567b6edc2a5be37529cf0a
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