Instructions to use pmczip/FLUX.1-dev_Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use pmczip/FLUX.1-dev_Models 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", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("pmczip/FLUX.1-dev_Models") prompt = "A portrait of 413xkin65t0n with curly auburn hair, captured in a candid moment. She is positioned against a backdrop of a cityscape, with buildings and trees visible in the distance. Her attire consists of a fitted, short-sleeved top and a plaid skirt. She gazes off to the side with a contemplative expression. The lighting suggests it might be either early morning or late afternoon, casting a soft glow on her freckled face. The overall mood of the image is serene and introspective. " image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Recently Added Flux.1-dev LoRa Models:
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# Z-Image Turbo LoRa Models
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<Gallery />
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