Instructions to use Salesforce/blip-image-captioning-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Salesforce/blip-image-captioning-base 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-base")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-base") model = AutoModelForMultimodalLM.from_pretrained("Salesforce/blip-image-captioning-base") - Notebooks
- Google Colab
- Kaggle
Update preprocessor_config.json
Browse files- preprocessor_config.json +0 -5
preprocessor_config.json
CHANGED
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{
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"do_normalize": true,
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"do_pad": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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0.48145466,
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0.27577711
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],
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"processor_class": "BlipProcessor",
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"resample": 3,
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"rescale_factor": 0.00392156862745098,
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"size": 384,
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"size_divisor": 32
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}
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{
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"do_normalize": true,
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"do_resize": true,
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"image_mean": [
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0.48145466,
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0.27577711
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],
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"processor_class": "BlipProcessor",
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"size": 384,
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}
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