Instructions to use quzo/newlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use quzo/newlora 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("quzo/newlora") prompt = "unconditional (blank prompt)" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit History
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Model card auto-generated by SimpleTuner
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Trained for 35 epochs and 900 steps.
Verified signatureTrained with datasets ['text-embeds', 'bartek-mizak-flux'] Learning rate 0.0001, batch size 1, and 1 gradient accumulation steps. Used DDPM noise scheduler for training with epsilon prediction type and rescaled_betas_zero_snr=False Using 'trailing' timestep spacing. Base model: black-forest-labs/FLUX.1-dev VAE: Nonedb6bae6 -
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Trained for 23 epochs and 600 steps.
Verified signatureTrained with datasets ['text-embeds', 'bartek-mizak-flux'] Learning rate 0.0001, batch size 1, and 1 gradient accumulation steps. Used DDPM noise scheduler for training with epsilon prediction type and rescaled_betas_zero_snr=False Using 'trailing' timestep spacing. Base model: black-forest-labs/FLUX.1-dev VAE: None564576e -
Validation images auto-generated by SimpleTuner
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Model card auto-generated by SimpleTuner
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Trained for 15 epochs and 400 steps.
Verified signatureTrained with datasets ['text-embeds', 'bartek-mizak-flux'] Learning rate 0.0001, batch size 1, and 1 gradient accumulation steps. Used DDPM noise scheduler for training with epsilon prediction type and rescaled_betas_zero_snr=False Using 'trailing' timestep spacing. Base model: black-forest-labs/FLUX.1-dev VAE: Nonebfca464 -
Validation images auto-generated by SimpleTuner
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Model card auto-generated by SimpleTuner
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Trained for 7 epochs and 200 steps.
Verified signatureTrained with datasets ['text-embeds', 'bartek-mizak-flux'] Learning rate 0.0001, batch size 1, and 1 gradient accumulation steps. Used DDPM noise scheduler for training with epsilon prediction type and rescaled_betas_zero_snr=False Using 'trailing' timestep spacing. Base model: black-forest-labs/FLUX.1-dev VAE: Nonef5fc2fa -
Validation images auto-generated by SimpleTuner
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initial commit
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