Instructions to use jetpackjules/supegen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jetpackjules/supegen with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jetpackjules/supegen", 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
Commit History
-
Add Diffusers weights
Add Diffusers weights converted from checkpoint `SuperGEN.ckpt` in revision a3b3fc66a6a389d0f7404f67c6b0cefa18bf54501848560
-
Upload sample_images with huggingface_hub
a3b3fc6 -
Upload model_index.json with huggingface_hub
52a2b5b -
Upload vae with huggingface_hub
fdc94ab -
Upload unet with huggingface_hub
8f7106b -
Upload tokenizer with huggingface_hub
dc707e0 -
Upload text_encoder with huggingface_hub
63bf406 -
Upload scheduler with huggingface_hub
cbf0fca -
Upload safety_checker with huggingface_hub
1d62422 -
Upload feature_extractor with huggingface_hub
23fc5b8 -
Upload the concept SupeGEN embeds and token
af63747 -
initial commit
7335eb8