Instructions to use diff-mining/g3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diff-mining/g3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diff-mining/g3", 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
- Draw Things
- DiffusionBee
- Xet hash:
- 62b07ebb7510b870a98f18d98af143d5992cfcbdb001fc6cb118bebde36c521c
- Size of remote file:
- 3.44 GB
- SHA256:
- d98161887c18ab119f1be8e36df99a4491402accde86bd2887809c707c5d064e
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