Instructions to use chungbv321/mlp-ginger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chungbv321/mlp-ginger 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("chungbv321/mlp-ginger") prompt = "mlp_ginger a cartoon cat wearing a pink shirt and blue shorts" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
mlp_ginger
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- mlp_ginger a cartoon cat wearing a pink shirt and blue shorts
Trigger words
You should use mlp_ginger 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 chungbv321/mlp-ginger
Base model
black-forest-labs/FLUX.1-dev