Instructions to use ThomasTKB/Flux-Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ThomasTKB/Flux-Lora 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("ThomasTKB/Flux-Lora") prompt = "tkbisfelt" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from ThomasTKB/Flux-Lora: direct link, hf CLI and curl.
- Browser
- Download file 719 Bytes
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https://huggingface.co/ThomasTKB/Flux-Lora/resolve/main/README.md
- Command line
-
hf download hf://ThomasTKB/Flux-Lora/README.md
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curl -L -o README.md https://huggingface.co/ThomasTKB/Flux-Lora/resolve/main/README.md
719 Bytes
metadata
tags:
- flux
- text-to-image
- lora
- diffusers
- fal
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: tkbisfelt
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
Flux Lora
Model description
Trigger words
You should use tkbisfelt 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.