Trained for 0 epochs and 1000 steps.

Trained with datasets ['text-embeds-pixart-filter', 'photo-concept-bucket', 'midjourney-v6-520k-raw', 'sfwbooru', 'nijijourney-v6-520k-raw', 'dalle3']
Learning rate 1e-06, batch size 24, 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: terminusresearch/pixart-900m-1024-ft-v0.6
VAE: madebyollin/sdxl-vae-fp16-fix

README.md

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+---
+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-vpred-zsnr
+
+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).
+
+
+
+
+<Gallery />
+
+The text encoder **was not** trained.
+You may reuse the base model text encoder for inference.
+
+
+## Training settings
+
+- Training epochs: 0
+- Training steps: 1000
+- 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
+### 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-vpred-zsnr'
+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")
+```
+

optimizer.bin

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+size 5451415117

random_states_0.pkl

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+size 16100

scheduler.bin

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+size 1000

training_state.json

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+{"global_step": 1000, "epoch_step": 1000, "epoch": 1, "exhausted_backends": [], "repeats": {}}

transformer/config.json

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+{
+  "_class_name": "PixArtTransformer2DModel",
+  "_diffusers_version": "0.30.0.dev0",
+  "_name_or_path": "terminusresearch/pixart-900m-1024-ft-v0.6",
+  "activation_fn": "gelu-approximate",
+  "attention_bias": true,
+  "attention_head_dim": 72,
+  "attention_type": "default",
+  "caption_channels": 4096,
+  "cross_attention_dim": 1152,
+  "double_self_attention": false,
+  "dropout": 0.0,
+  "in_channels": 4,
+  "interpolation_scale": 2,
+  "norm_elementwise_affine": false,
+  "norm_eps": 1e-06,
+  "norm_num_groups": 32,
+  "norm_type": "ada_norm_single",
+  "num_attention_heads": 16,
+  "num_embeds_ada_norm": 1000,
+  "num_layers": 42,
+  "num_vector_embeds": null,
+  "only_cross_attention": false,
+  "out_channels": 8,
+  "patch_size": 2,
+  "sample_size": 128,
+  "upcast_attention": false,
+  "use_additional_conditions": false,
+  "use_linear_projection": false
+}

transformer/diffusion_pytorch_model.safetensors

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