Instructions to use Salesforce/blip-image-captioning-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Salesforce/blip-image-captioning-large 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/blip-image-captioning-large")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-large") model = AutoModelForImageTextToText.from_pretrained("Salesforce/blip-image-captioning-large") - Notebooks
- Google Colab
- Kaggle
Update README.md
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by dacquaviva - opened
README.md
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@@ -72,7 +72,7 @@ from PIL import Image
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from transformers import BlipProcessor, BlipForConditionalGeneration
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processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
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model = BlipForConditionalGeneration.from_pretrained("
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img_url = 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/demo.jpg'
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raw_image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')
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from transformers import BlipProcessor, BlipForConditionalGeneration
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processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-large")
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model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-large").to("cuda")
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img_url = 'https://storage.googleapis.com/sfr-vision-language-research/BLIP/demo.jpg'
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raw_image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')
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