Instructions to use danielsv/EmiLoras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use danielsv/EmiLoras 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("danielsv/EmiLoras") prompt = "emi dancing in the street" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
EmiLoras
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- emi dancing in the street

- Prompt
- emi in the garden

- Prompt
- emi running in the street

- Prompt
- emi in the kitchen
Trigger words
You should use emi 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 danielsv/EmiLoras
Base model
black-forest-labs/FLUX.1-dev