Text-to-Image
Diffusers
English
StableDiffusionPipeline
dreambooth
stable-diffusion
stable-diffusion-diffusers
Instructions to use lambda/dreambooth-avatar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lambda/dreambooth-avatar with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lambda/dreambooth-avatar", 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
- Xet hash:
- a595416885ab97cb13736bf2d0145ed5764cfb9806f74eb5330d21c15878b069
- Size of remote file:
- 3.46 GB
- SHA256:
- e829045c606f47355cdbc707683a6a254a34db7cbad4f100eb4197c1a2d51671
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.