Instructions to use ping-ping/disdog-style-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ping-ping/disdog-style-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ping-ping/disdog-style-lora") prompt = "a DISDOGSTYLE style dog in the pool" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
disdog-style-lora
Model trained with AI Toolkit by Ostris

- Prompt
- a DISDOGSTYLE style dog in the pool

- Prompt
- DISDOGSTYLE style dog family happily playing in the park

- Prompt
- a DISDOGSTYLE style dog with a red collar
Trigger words
You should use DISDOGSTYLE to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('ping-ping/disdog-style-lora', weight_name='disdog-style-lora')
image = pipeline('a DISDOGSTYLE style dog in the pool').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
- Downloads last month
- 24
Model tree for ping-ping/disdog-style-lora
Base model
black-forest-labs/FLUX.1-dev