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:
- 34de795e4561069a554409d57a1963b5abfb3cc55e9730973894d028716f7b75
- Size of remote file:
- 6.33 GB
- SHA256:
- afef3d90827b19571700dc3cf3ce403b34ae35cbc2137d0b772660af4115d804
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