Instructions to use RockyRocks/Swathi-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RockyRocks/Swathi-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("lodestones/Chroma1-Base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("RockyRocks/Swathi-lora") prompt = "Sw@th!" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Swathi-lora
Model trained with AI Toolkit by Ostris
Trigger words
You should use Sw@th! 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('lodestones/Chroma1-Base', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('RockyRocks/Swathi-lora', weight_name='Swathi_000001750.safetensors')
image = pipeline('Sw@th!').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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Model tree for RockyRocks/Swathi-lora
Base model
lodestones/Chroma1-Base