Instructions to use brianpk80/RTK4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use brianpk80/RTK4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3.5-large", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("brianpk80/RTK4") prompt = "RTK" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
license: other
license_name: stabilityai-ai-community
license_link: >-
https://huggingface.co/stabilityai/stable-diffusion-3.5-large/blob/main/LICENSE.md
language:
- en
tags:
- sd3.5-large
- diffusers
- lora
- replicate
base_model: stabilityai/stable-diffusion-3.5-large
pipeline_tag: text-to-image
instance_prompt: RTK
Rtk4
Trained on Replicate using:
https://replicate.com/lucataco/sd3.5-fine-tuner/train
Trigger words
You should use RTK to trigger the image generation.
Use it with the 🧨 diffusers library
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers