Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use zhengzhou/checkpoints_lyf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zhengzhou/checkpoints_lyf with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("zhengzhou/checkpoints_lyf", dtype=torch.bfloat16, device_map="cuda") prompt = "a realistic photo of lyf woman" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
DreamBooth - zhengzhou/checkpoints_lyf
This is a dreambooth model derived from SG161222/Realistic_Vision_V2.0. The weights were trained on a realistic photo of lyf woman using DreamBooth. You can find some example images in the following.
DreamBooth for the text encoder was enabled: False.
- Downloads last month
- 1
Model tree for zhengzhou/checkpoints_lyf
Base model
SG161222/Realistic_Vision_V2.0