Instructions to use FloydianSound/Redline_Diffusion_V1-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FloydianSound/Redline_Diffusion_V1-5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FloydianSound/Redline_Diffusion_V1-5", 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 text_encoder/pytorch_model.bin from FloydianSound/Redline_Diffusion_V1-5: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/FloydianSound/Redline_Diffusion_V1-5/resolve/refs%2Fpr%2F3/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://FloydianSound/Redline_Diffusion_V1-5@refs/pr/3/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/FloydianSound/Redline_Diffusion_V1-5/resolve/refs%2Fpr%2F3/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- d07df4014e8790455eaa7ba0aa9fe239fa82d224f1b71b5b51ddc6a2fa1e7ac0
- Size of remote file:
- 492 MB
- SHA256:
- 0d114d9e3ad8970033b2aa8935ce51b05f69fa2356c76e561b8b280060450a3d
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