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--- |
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license: creativeml-openrail-m |
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base_model: "black-forest-labs/FLUX.1-dev" |
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tags: |
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- stable-diffusion |
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- stable-diffusion-diffusers |
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- text-to-image |
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- diffusers |
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- simpletuner |
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- lora |
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- template:sd-lora |
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inference: true |
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--- |
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# ohwx-man |
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This is a LoRA derived from [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev). |
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The main validation prompt used during training was: |
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``` |
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a photograph of ohwx man |
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``` |
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## Validation settings |
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- CFG: `3.5` |
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- CFG Rescale: `0.0` |
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- Steps: `28` |
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- Sampler: `None` |
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- Seed: `42` |
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- Resolution: `1024` |
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Note: The validation settings are not necessarily the same as the [training settings](#training-settings). |
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<Gallery /> |
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The text encoder **was not** trained. |
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You may reuse the base model text encoder for inference. |
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## Training settings |
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- Training epochs: 499 |
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- Training steps: 500 |
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- Learning rate: 0.0001 |
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- Effective batch size: 4 |
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- Micro-batch size: 1 |
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- Gradient accumulation steps: 4 |
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- Number of GPUs: 1 |
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- Prediction type: flow-matching |
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- Rescaled betas zero SNR: False |
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- Optimizer: AdamW, stochastic bf16 |
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- Precision: Pure BF16 |
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- Quantised: Yes: int8-quanto |
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- Xformers: Not used |
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- LoRA Rank: 16 |
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- LoRA Alpha: None |
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- LoRA Dropout: 0.1 |
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- LoRA initialisation style: default |
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## Datasets |
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### ohwx-man-v3 |
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- Repeats: 0 |
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- Total number of images: 4 |
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- Total number of aspect buckets: 1 |
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- Resolution: 512 px |
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- Cropped: False |
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- Crop style: None |
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- Crop aspect: None |
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## Inference |
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```python |
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import torch |
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from diffusers import DiffusionPipeline |
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model_id = 'black-forest-labs/FLUX.1-dev' |
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adapter_id = 'AA12312424/ohwx-man' |
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pipeline = DiffusionPipeline.from_pretrained(model_id) |
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pipeline.load_lora_weights(adapter_id) |
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prompt = "a photograph of ohwx man" |
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pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') |
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image = pipeline( |
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prompt=prompt, |
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num_inference_steps=28, |
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generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826), |
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width=1024, |
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height=1024, |
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guidance_scale=3.5, |
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).images[0] |
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image.save("output.png", format="PNG") |
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``` |
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