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
Download model.bin from JD97/Riffusion_sentiment_LoRA: direct link, hf CLI and curl.
- Browser
- Download file 427 Bytes
-
https://huggingface.co/JD97/Riffusion_sentiment_LoRA/resolve/main/model.bin
- Command line
-
hf download hf://JD97/Riffusion_sentiment_LoRA/model.bin
-
curl -L -o model.bin https://huggingface.co/JD97/Riffusion_sentiment_LoRA/resolve/main/model.bin
427 Bytes
- Xet hash:
- 8d58736480f0f340e0e927b7716ddeeb257c4975e5aa3eb5b2d4a9f52570bfce
- Size of remote file:
- 427 Bytes
- SHA256:
- 498d78a878af05b7278e474ae1364a7218026c8f8b02f920339fc5c7dd59661a
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