Instructions to use codemanCheng/sd_1.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codemanCheng/sd_1.5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("codemanCheng/sd_1.5") prompt = "a photo of sks cat" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
license: creativeml-openrail-m
base_model: /home/cas/stable-diffusion-v1-5
instance_prompt: a photo of sks cat
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- lora
inference: true
LoRA DreamBooth - codemanCheng/sd_1.5
These are LoRA adaption weights for /home/cas/stable-diffusion-v1-5. The weights were trained on a photo of sks cat using DreamBooth. You can find some example images in the following.
LoRA for the text encoder was enabled: True.



