Instructions to use Akbartus/SimpleVectorFlux_LORA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Akbartus/SimpleVectorFlux_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("Akbartus/SimpleVectorFlux_LORA") prompt = "v3ct0r" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Create README.md
Browse files
README.md
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---
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tags:
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- text-to-image
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- flux
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- lora
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- diffusers
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- template:sd-lora
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- ai-toolkit
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base_model: black-forest-labs/FLUX.1-dev
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instance_prompt: 'v3ct0r'
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license: other
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license_name: flux-1-dev-non-commercial-license
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license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
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---
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