Instructions to use Sagardai/m2st2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Sagardai/m2st2 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("Sagardai/m2st2") prompt = "m2st2, Bally1a a tiger playing chess --d5567" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
m2st2
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- m2st2, Bally1a a tiger playing chess --d5567

- Prompt
- m2st2, Astar2b a tiger playing football --d5567

- Prompt
- m2st2, Astar2b a tiger riding bike --d5567

- Prompt
- m2st2, Bally1a a tiger eating cake --d5567
Trigger words
You should use m2st2 to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, Forge, etc.
Weights for this model are available in Safetensors format.
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Model tree for Sagardai/m2st2
Base model
black-forest-labs/FLUX.1-dev