--- license: creativeml-openrail-m base_model: "terminusresearch/pixart-900m-1024-ft-v0.6" tags: - stable-diffusion - stable-diffusion-diffusers - text-to-image - diffusers - simpletuner - full inference: true --- # pixart-900m-1024-ft-v0.7-stage1 This is a full rank finetune derived from [terminusresearch/pixart-900m-1024-ft-v0.6](https://huggingface.co/terminusresearch/pixart-900m-1024-ft-v0.6). The main validation prompt used during training was: ``` ethnographic photography of teddy bear at a picnic, ears tucked behind a cozy hoodie looking darkly off to the stormy picnic skies ``` ## Validation settings - CFG: `7.5` - CFG Rescale: `0.7` - Steps: `25` - Sampler: `None` - Seed: `42` - Resolutions: `1024x1024,1344x768,916x1152` Note: The validation settings are not necessarily the same as the [training settings](#training-settings). The text encoder **was not** trained. You may reuse the base model text encoder for inference. ## Training settings - Training epochs: 0 - Training steps: 17000 - Learning rate: 1e-06 - Effective batch size: 192 - Micro-batch size: 24 - Gradient accumulation steps: 1 - Number of GPUs: 8 - Prediction type: epsilon - Rescaled betas zero SNR: False - Optimizer: AdamW, stochastic bf16 - Precision: Pure BF16 - Xformers: Not used ## Datasets ### photo-concept-bucket - Repeats: 0 - Total number of images: ~567552 - Total number of aspect buckets: 1 - Resolution: 1.0 megapixels - Cropped: True - Crop style: random - Crop aspect: square ### text-1mp - Repeats: 15 - Total number of images: ~13056 - Total number of aspect buckets: 1 - Resolution: 1.0 megapixels - Cropped: True - Crop style: random - Crop aspect: square ### ideogram - Repeats: 15 - Total number of images: ~36096 - Total number of aspect buckets: 1 - Resolution: 1.0 megapixels - Cropped: True - Crop style: random - Crop aspect: square ### midjourney-v6-520k-raw - Repeats: 0 - Total number of images: ~390912 - Total number of aspect buckets: 1 - Resolution: 1.0 megapixels - Cropped: True - Crop style: random - Crop aspect: square ### sfwbooru - Repeats: 0 - Total number of images: ~233664 - Total number of aspect buckets: 1 - Resolution: 1.0 megapixels - Cropped: True - Crop style: random - Crop aspect: square ### nijijourney-v6-520k-raw - Repeats: 0 - Total number of images: ~415680 - Total number of aspect buckets: 1 - Resolution: 1.0 megapixels - Cropped: True - Crop style: random - Crop aspect: square ### dalle3 - Repeats: 0 - Total number of images: ~1121664 - Total number of aspect buckets: 1 - Resolution: 1.0 megapixels - Cropped: True - Crop style: random - Crop aspect: square ## Inference ```python import torch from diffusers import DiffusionPipeline model_id = 'pixart-900m-1024-ft-v0.7-stage1' pipeline = DiffusionPipeline.from_pretrained(model_id) prompt = "ethnographic photography of teddy bear at a picnic, ears tucked behind a cozy hoodie looking darkly off to the stormy picnic skies" negative_prompt = "blurry, cropped, ugly" pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu') image = pipeline( prompt=prompt, negative_prompt='blurry, cropped, ugly', num_inference_steps=25, generator=torch.Generator(device='cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu').manual_seed(1641421826), width=1152, height=768, guidance_scale=7.5, guidance_rescale=0.7, ).images[0] image.save("output.png", format="PNG") ```