Instructions to use yvesfogel/chelomac with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yvesfogel/chelomac 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("yvesfogel/chelomac") prompt = "This is a photo of CHELOMAC wearing a blue shirt, with a friendly smile, against a neutral gray background. The CHELOMAC has a relaxed posture, with soft, even lighting highlighting the details." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
CHELOMAC
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- This is a photo of CHELOMAC wearing a blue shirt, with a friendly smile, against a neutral gray background. The CHELOMAC has a relaxed posture, with soft, even lighting highlighting the details.

- Prompt
- This image shows CHELOMAC with a joyful smile, wearing a gray hoodie with bold black text and a blue surgical mask pulled down to the chin. The background is an urban setting with buildings and greenery, under overcast lighting.
Trigger words
You should use CHELOMAC 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 yvesfogel/chelomac
Base model
black-forest-labs/FLUX.1-dev