Instructions to use SE6446/Untitled7-colab_checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SE6446/Untitled7-colab_checkpoint 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="SE6446/Untitled7-colab_checkpoint")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("SE6446/Untitled7-colab_checkpoint") model = AutoModelForImageTextToText.from_pretrained("SE6446/Untitled7-colab_checkpoint") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -15,6 +15,8 @@ This model was lovingly named after the Google Colab notebook that made it. It i
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It is supposed to read images and extract a stable diffusion prompt from it but, it might not do a good job at it. I wouldn't know I haven't extensivly tested it.
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As the title suggests this is a checkpoint as I formerly intended to do it on the entire dataset but, I'm unsure if I want to now...
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## Intended use
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Fun!
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It is supposed to read images and extract a stable diffusion prompt from it but, it might not do a good job at it. I wouldn't know I haven't extensivly tested it.
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As the title suggests this is a checkpoint as I formerly intended to do it on the entire dataset but, I'm unsure if I want to now...
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This is my first public model so please be nice!
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## Intended use
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Fun!
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