Instructions to use flax/redshift-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use flax/redshift-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("flax/redshift-diffusion", 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/flax_model.msgpack from flax/redshift-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/flax/redshift-diffusion/resolve/refs%2Fpr%2F3/text_encoder/flax_model.msgpack
- Command line
-
hf download hf://flax/redshift-diffusion@refs/pr/3/text_encoder/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/flax/redshift-diffusion/resolve/refs%2Fpr%2F3/text_encoder/flax_model.msgpack
492 MB
- Xet hash:
- 7a6600210e9d89dd5911d5916a8f363c34afb9e90cd8aa9fea297adb9573a5c3
- Size of remote file:
- 492 MB
- SHA256:
- 08114ac3e87871eb3c108c0f73c395f30c04574bf9d2a6911eec049be029c6c2
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