Instructions to use Muhammadreza/atelierportraits with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muhammadreza/atelierportraits 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/atelierportraits") prompt = "A young blonde woman in a bustling cafe atelier_prtrt" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
atelierportraits
Model trained with AI Toolkit by Ostris

- Prompt
- A young blonde woman in a bustling cafe atelier_prtrt

- Prompt
- A young man wearing a suit, a city in the background, atelier_prtrt
Trigger words
You should use atelier_prtrt 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/atelierportraits', weight_name='atelierportraits.safetensors')
image = pipeline('A young blonde woman in a bustling cafe atelier_prtrt').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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Model tree for Muhammadreza/atelierportraits
Base model
black-forest-labs/FLUX.1-dev