Instructions to use Brainergy/betroco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Brainergy/betroco with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Brainergy/betroco", 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
d0b7508 -
Upload model_index.json with huggingface_hub
02265f5 -
Upload vae with huggingface_hub
f73d863 -
Upload unet with huggingface_hub
ff00b28 -
Upload tokenizer with huggingface_hub
715f7e1 -
Upload text_encoder with huggingface_hub
95f33b9 -
Upload scheduler with huggingface_hub
f26b8d2 -
Upload feature_extractor with huggingface_hub
74b739d -
Upload the concept betroco embeds and token
f37f7b8 -
initial commit
ef5fe0c