Instructions to use Fred99774/descoledra with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Fred99774/descoledra with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Fred99774/descoledra", 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
-
Upload sample_images with huggingface_hub
a836395 -
Upload model_index.json with huggingface_hub
f3c7773 -
Upload vae with huggingface_hub
df44565 -
Upload unet with huggingface_hub
ee367c7 -
Upload tokenizer with huggingface_hub
f86f7ca -
Upload text_encoder with huggingface_hub
5a3d82e -
Upload scheduler with huggingface_hub
77cda81 -
Upload feature_extractor with huggingface_hub
9bd69cd -
Upload the concept descoledra embeds and token
2d1f8a6 -
initial commit
2769175