Image-to-Text
Transformers
PyTorch
Safetensors
English
blip-2
visual-question-answering
vision
image-captioning
Instructions to use Salesforce/blip2-opt-2.7b-coco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Salesforce/blip2-opt-2.7b-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-opt-2.7b-coco")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Salesforce/blip2-opt-2.7b-coco") model = AutoModelForMultimodalLM.from_pretrained("Salesforce/blip2-opt-2.7b-coco") - Notebooks
- Google Colab
- Kaggle
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tags:
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- vision
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- image-to-text
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pipeline_tag: image-to-text
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---
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# BLIP-2, OPT-2.7b, fine-tuned on COCO
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tags:
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- vision
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- image-to-text
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- image-captioning
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- visual-question-answering
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pipeline_tag: image-to-text
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inference: false
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---
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# BLIP-2, OPT-2.7b, fine-tuned on COCO
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