toilaluan commited on
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Trained for 4 epochs and 45 steps.

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Trained with datasets ['text-embeds', 'xxx123']
Learning rate 8e-07, batch size 10, and 4 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: toilaluan/turbox
VAE: madebyollin/sdxl-vae-fp16-fix

README.md ADDED
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+ ---
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+ license: creativeml-openrail-m
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+ base_model: "toilaluan/turbox"
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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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+ - full
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+
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+ inference: true
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+
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+ ---
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+
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+ # full-training
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+
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+ This is a full rank finetune derived from [toilaluan/turbox](https://huggingface.co/toilaluan/turbox).
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+
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+
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+
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+ The main validation prompt used during training was:
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+
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+ ```
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+ ethnographic photography of teddy bear at a picnic
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+ ```
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+
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+ ## Validation settings
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+ - CFG: `7.5`
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+ - CFG Rescale: `0.0`
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+ - Steps: `30`
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+ - Sampler: `None`
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+ - Seed: `42`
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+ - Resolution: `1024`
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+
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+ Note: The validation settings are not necessarily the same as the [training settings](#training-settings).
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+
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+
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+
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+
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+ <Gallery />
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+
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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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+
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+
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+ ## Training settings
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+
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+ - Training epochs: 4
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+ - Training steps: 45
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+ - Learning rate: 8e-07
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+ - Effective batch size: 40
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+ - Micro-batch size: 10
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+ - Gradient accumulation steps: 4
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+ - Number of GPUs: 1
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+ - Prediction type: epsilon
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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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+ - Xformers: Not used
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+
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+
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+ ## Datasets
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+
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+ ### xxx123
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+ - Repeats: 0
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+ - Total number of images: 360
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+ - Total number of aspect buckets: 1
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+ - Resolution: 1.0 megapixels
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+ - Cropped: False
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+ - Crop style: None
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+ - Crop aspect: None
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+
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+
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+ ## Inference
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+
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+
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+ ```python
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+ import torch
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+ from diffusers import DiffusionPipeline
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+
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+ model_id = 'full-training'
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+ pipeline = DiffusionPipeline.from_pretrained(model_id)
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+
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+ prompt = "ethnographic photography of teddy bear at a picnic"
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+ negative_prompt = "blurry, cropped, ugly"
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+
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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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+ negative_prompt='blurry, cropped, ugly',
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+ num_inference_steps=30,
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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=1152,
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+ height=768,
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+ guidance_scale=7.5,
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+ guidance_rescale=0.0,
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+ ).images[0]
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+ image.save("output.png", format="PNG")
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+ ```
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+
model_index.json ADDED
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+ {
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+ "_class_name": "StableDiffusionXLPipeline",
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+ "_diffusers_version": "0.30.0.dev0",
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+ "_name_or_path": "toilaluan/turbox",
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+ "feature_extractor": [
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+ "force_zeros_for_empty_prompt": true,
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+ "image_encoder": [
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+ "scheduler": [
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+ "diffusers",
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+ "EulerDiscreteScheduler"
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+ ],
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+ "text_encoder": [
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+ "tokenizer": [
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+ "transformers",
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+ "CLIPTokenizer"
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+ "transformers",
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+ "CLIPTokenizer"
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+ ],
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+ "unet": [
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+ "diffusers",
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+ "UNet2DConditionModel"
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+ ],
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+ "vae": [
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+ "diffusers",
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+ "AutoencoderKL"
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+ ]
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+ }
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+ "prediction_type": "epsilon",
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