Instructions to use braintacles/brainblip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use braintacles/brainblip 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="braintacles/brainblip")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("braintacles/brainblip") model = AutoModelForImageTextToText.from_pretrained("braintacles/brainblip") - Notebooks
- Google Colab
- Kaggle
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README.md
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# BrainBLIP
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**This model is not ready for production use and is in preliminary stages of training. Use at your own risks**
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## Model Details
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### Model Description
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BrainBLIP is finetuned to give more natural captions for training text-to-image datasets with an emphasis on natural language while adding a minimal amount of tags for context.
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This model also introduces "movie rating" tags similar to [what CivitAI has implemented](https://education.civitai.com/civitais-guide-to-content-levels/):
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- PG_RATING
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- PG13_RATING
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- R_RATING
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- X_RATING
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- XXX_RATING
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The model needs a lot more data so these tags are not quite consistent yet.
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## How to Get Started with the Model
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# BrainBLIP
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**This model is not ready for production use and is in preliminary stages of training. Use at your own risks**
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### Model Description
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BrainBLIP is finetuned to give more natural captions for training text-to-image datasets with an emphasis on natural language while adding a minimal amount of tags for context.
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## How to Get Started with the Model
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