Instructions to use Muhammadreza/mahdis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muhammadreza/mahdis 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("Muhammadreza/mahdis") prompt = "cowboy wearing a denim jacket, atelierai_sks_768" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
mahdis_parpanchi
Model trained with AI Toolkit by Ostris

- Prompt
- cowboy wearing a denim jacket, atelierai_sks_768
Trigger words
You should use atelierai_sks_768 to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('Muhammadreza/mahdis', weight_name='mahdis_parpanchi.safetensors')
image = pipeline('cowboy wearing a denim jacket, atelierai_sks_768').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
- Downloads last month
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Model tree for Muhammadreza/mahdis
Base model
black-forest-labs/FLUX.1-dev