Instructions to use bodam/model_lora5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bodam/model_lora5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("bodam/model_lora5") prompt = "a olis chair" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
license: creativeml-openrail-m
base_model: runwayml/stable-diffusion-v1-5
instance_prompt: a olis chair
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- lora
inference: true
LoRA DreamBooth - bodam/model_lora5
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on a olis chair using DreamBooth. You can find some example images in the following.



