Trained for 0 epochs and 200 steps.

Trained with datasets ['text-embeds', 'celebrities', 'movieposters', 'normalnudes', 'moviecollection', 'experimental', 'ethnic', 'gay', 'cinemamix-1mp', 'nsfw-1024']
Learning rate 1e-06, batch size 16, and 1 gradient accumulation steps.
Used DDPM noise scheduler for training with epsilon prediction type and rescaled_betas_zero_snr=False
Using 'linspace' timestep spacing.
Base model: terminusresearch/pixart-900m-1024-ft-v0.6
VAE: madebyollin/sdxl-vae-fp16-fix

README.md

@@ -0,0 +1,165 @@
+---
+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-stage2
+
+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:
+
+```
+a cute anime character named toast, holding a sign that reads SOON
+```
+
+## Validation settings
+- CFG: `7.5`
+- CFG Rescale: `0.7`
+- Steps: `30`
+- Sampler: `None`
+- Seed: `420420420`
+- Resolutions: `1024x1024,1152x960,896x1152`
+
+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: 200
+- Learning rate: 1e-06
+- Effective batch size: 16
+  - Micro-batch size: 16
+  - Gradient accumulation steps: 1
+  - Number of GPUs: 1
+- Prediction type: epsilon
+- Rescaled betas zero SNR: False
+- Optimizer: AdamW, stochastic bf16
+- Precision: Pure BF16
+- Xformers: Enabled
+
+
+## Datasets
+
+### celebrities
+- Repeats: 4
+- Total number of images: 208
+- Total number of aspect buckets: 5
+- Resolution: 1.0 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+### movieposters
+- Repeats: 25
+- Total number of images: 192
+- Total number of aspect buckets: 3
+- Resolution: 1.0 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+### normalnudes
+- Repeats: 5
+- Total number of images: 992
+- Total number of aspect buckets: 2
+- Resolution: 1.0 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+### moviecollection
+- Repeats: 0
+- Total number of images: 1744
+- Total number of aspect buckets: 12
+- Resolution: 1.0 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+### experimental
+- Repeats: 0
+- Total number of images: 2816
+- Total number of aspect buckets: 3
+- Resolution: 1.0 megapixels
+- Cropped: True
+- Crop style: random
+- Crop aspect: random
+### ethnic
+- Repeats: 0
+- Total number of images: 1808
+- Total number of aspect buckets: 3
+- Resolution: 1.0 megapixels
+- Cropped: True
+- Crop style: random
+- Crop aspect: random
+### gay
+- Repeats: 0
+- Total number of images: 768
+- Total number of aspect buckets: 2
+- Resolution: 1.0 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+### cinemamix-1mp
+- Repeats: 0
+- Total number of images: 7376
+- Total number of aspect buckets: 5
+- Resolution: 1.0 megapixels
+- Cropped: False
+- Crop style: None
+- Crop aspect: None
+### nsfw-1024
+- Repeats: 0
+- Total number of images: 2224
+- Total number of aspect buckets: 3
+- Resolution: 1.0 megapixels
+- Cropped: True
+- Crop style: random
+- Crop aspect: random
+
+
+## Inference
+
+
+```python
+import torch
+from diffusers import DiffusionPipeline
+
+model_id = 'pixart-900m-1024-ft-v0.7-stage2'
+pipeline = DiffusionPipeline.from_pretrained(model_id)
+
+prompt = "a cute anime character named toast, holding a sign that reads SOON"
+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=30,
+    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 14344

scheduler.bin

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+oid sha256:8b208965b935eb8cd950babb1e77513fba53c09565fd227dd4a8425900fbeb57
+size 1000

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training_state.json

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transformer/config.json

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+  "_diffusers_version": "0.30.0.dev0",
+  "_name_or_path": "terminusresearch/pixart-900m-1024-ft-v0.6",
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+  "attention_type": "default",
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+  "norm_type": "ada_norm_single",
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+  "num_embeds_ada_norm": 1000,
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+}

transformer/diffusion_pytorch_model.safetensors

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