Instructions to use davidjaymes/dj_flux-lora-fast_anat-true with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use davidjaymes/dj_flux-lora-fast_anat-true 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("davidjaymes/dj_flux-lora-fast_anat-true") prompt = "anat-true" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
dj_flux lora fast_anat true
Model description
Custom LoRa trained on Fal.ai for "anat-true", an AV star.
Trigger words
You should use anat-true to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Training at fal.ai
Training was done using fal.ai/models/fal-ai/flux-lora-fast-training.
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Model tree for davidjaymes/dj_flux-lora-fast_anat-true
Base model
black-forest-labs/FLUX.1-dev