Instructions to use JD97/Riffusion_sentiment_LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JD97/Riffusion_sentiment_LoRA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JD97/Riffusion_sentiment_LoRA", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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README.md
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---
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### Introduce
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Riffusion with LoRA, fine-tuned with <code>Chr0my/Epidemic_music</code>
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This model was used during Naver Connect BoostCamp AI tech 4th, NLP Track
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### Citation
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- text-to-audio
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---
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### Introduce
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Riffusion with LoRA, fine-tuned with <code>Chr0my/Epidemic_music</code> <br/>
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This model was used during Naver Connect BoostCamp AI tech 4th, NLP Track
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### Citation
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