End of training
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- README.md +46 -0
- checkpoint-14500/optimizer.bin +3 -0
- checkpoint-14500/random_states_0.pkl +3 -0
- checkpoint-14500/scaler.pt +3 -0
- checkpoint-14500/scheduler.bin +3 -0
- checkpoint-14500/unet/config.json +67 -0
- checkpoint-14500/unet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-14500/unet_ema/config.json +74 -0
- checkpoint-14500/unet_ema/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-15000/optimizer.bin +3 -0
- checkpoint-15000/random_states_0.pkl +3 -0
- checkpoint-15000/scaler.pt +3 -0
- checkpoint-15000/scheduler.bin +3 -0
- checkpoint-15000/unet/config.json +67 -0
- checkpoint-15000/unet/diffusion_pytorch_model.safetensors +3 -0
- checkpoint-15000/unet_ema/config.json +74 -0
- checkpoint-15000/unet_ema/diffusion_pytorch_model.safetensors +3 -0
- feature_extractor/preprocessor_config.json +28 -0
- logs/text2image-fine-tune/1696858589.9366672/events.out.tfevents.1696858589.aa1d505ac963.3709.1 +3 -0
- logs/text2image-fine-tune/1696858589.9385805/hparams.yml +50 -0
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- logs/text2image-fine-tune/1696868286.757576/hparams.yml +50 -0
- logs/text2image-fine-tune/1696868333.0287201/events.out.tfevents.1696868333.aa1d505ac963.43737.1 +3 -0
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- logs/text2image-fine-tune/events.out.tfevents.1696890174.aa1d505ac963.133152.0 +3 -0
README.md
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---
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license: creativeml-openrail-m
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base_model: CompVis/stable-diffusion-v1-4
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datasets:
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- Skiittoo/cartoon-faces
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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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inference: true
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---
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# Text-to-image finetuning - Skiittoo/sd-cartoon-faces-model
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This pipeline was finetuned from **CompVis/stable-diffusion-v1-4** on the **Skiittoo/cartoon-faces** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['[Cartoon face with white skin]']:
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## Pipeline usage
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You can use the pipeline like so:
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```python
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from diffusers import DiffusionPipeline
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import torch
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pipeline = DiffusionPipeline.from_pretrained("Skiittoo/sd-cartoon-faces-model", torch_dtype=torch.float16)
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prompt = "[Cartoon face with white skin]"
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image = pipeline(prompt).images[0]
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image.save("my_image.png")
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```
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## Training info
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These are the key hyperparameters used during training:
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* Epochs: 6
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* Learning rate: 1e-05
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* Batch size: 1
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* Gradient accumulation steps: 4
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* Image resolution: 512
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* Mixed-precision: fp16
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checkpoint-14500/optimizer.bin
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checkpoint-14500/random_states_0.pkl
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checkpoint-14500/scaler.pt
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checkpoint-14500/unet/config.json
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{
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"_class_name": "UNet2DConditionModel",
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"_diffusers_version": "0.22.0.dev0",
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"_name_or_path": "sd-cartoon-faces-model/checkpoint-11500",
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"act_fn": "silu",
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"attention_type": "default",
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"down_block_types": [
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"mid_block_scale_factor": 1,
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"mid_block_type": "UNetMidBlock2DCrossAttn",
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"norm_eps": 1e-05,
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"up_block_types": [
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checkpoint-14500/unet/diffusion_pytorch_model.safetensors
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checkpoint-14500/unet_ema/config.json
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checkpoint-14500/unet_ema/diffusion_pytorch_model.safetensors
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checkpoint-15000/unet_ema/config.json
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checkpoint-15000/unet_ema/diffusion_pytorch_model.safetensors
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logs/text2image-fine-tune/1696858589.9385805/hparams.yml
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version https://git-lfs.github.com/spec/v1
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oid sha256:730b3f7002e54c62f0e63966be96d147162979a6d9ff38ee072d35abfb48b84e
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size 171588
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logs/text2image-fine-tune/events.out.tfevents.1696890174.aa1d505ac963.133152.0
ADDED
@@ -0,0 +1,3 @@
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|
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|
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|
1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:d21c0a038c45bf91669c74284d3705ed45c87a34a104b40aa3fd3f8b4298080d
|
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+
size 88
|