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
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by anon-repair-bot - opened
README.md
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@@ -121,7 +121,7 @@ inputs = processor(raw_image, return_tensors="pt").to("cuda", torch.float16)
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out = model.generate(**inputs)
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print(processor.decode(out[0], skip_special_tokens=True))
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>>> a woman sitting on the beach with her dog
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```
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</details>
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out = model.generate(**inputs)
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print(processor.decode(out[0], skip_special_tokens=True))
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# >>> a woman sitting on the beach with her dog
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```
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</details>
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