Text-to-Image
Diffusers
stable-diffusion
stable-diffusion-diffusers
simpletuner
lora
template:sd-lora
Instructions to use machachu56/flux-daiki with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use machachu56/flux-daiki 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("machachu56/flux-daiki") 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 18 epochs and 400 steps.
Verified signatureTrained with datasets ['text-embeds', 'default_dataset'] Learning rate 0.0001, batch size 2, 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: None0706bd3 -
Validation images auto-generated by SimpleTuner
Verified signature3a92c6c
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Model card auto-generated by SimpleTuner
Verified signature250b3d4 -
Trained for 9 epochs and 200 steps.
Verified signatureTrained with datasets ['text-embeds', 'default_dataset'] Learning rate 0.0001, batch size 2, 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: None206bf6b -
Validation images auto-generated by SimpleTuner
Verified signature66ea94d -
initial commit
Verified signatureb44639f