Text-to-Image
Diffusers
Trained with AutoTrain
stable-diffusion
stable-diffusion-diffusers
lora
template:sd-lora
Instructions to use elchileno/bad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use elchileno/bad 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("elchileno/bad") prompt = "a cartoon drawing of" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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("elchileno/bad")
prompt = "a cartoon drawing of"
image = pipe(prompt).images[0]AutoTrain LoRA DreamBooth - elchileno/bad
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on a cartoon drawing of using DreamBooth. LoRA for the text encoder was enabled: False.
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Model tree for elchileno/bad
Base model
runwayml/stable-diffusion-v1-5