Instructions to use ifmain/blip-image2promt-stable-diffusion-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ifmain/blip-image2promt-stable-diffusion-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="ifmain/blip-image2promt-stable-diffusion-base")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("ifmain/blip-image2promt-stable-diffusion-base") model = AutoModelForMultimodalLM.from_pretrained("ifmain/blip-image2promt-stable-diffusion-base") - Notebooks
- Google Colab
- Kaggle
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README.md
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license: mit
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datasets:
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pipeline_tag: image-to-text
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base_model: Salesforce/blip-image-captioning-base
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## Addition
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This model support SFW and NSFW content
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datasets:
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- Ar4ikov/civitai-sd-337k
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language:
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- en
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pipeline_tag: image-to-text
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base_model: Salesforce/blip-image-captioning-base
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## Addition
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This model support SFW and NSFW content
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