End of training
Browse files- README.md +79 -0
- checkpoint-3000/optimizer.bin +3 -0
- checkpoint-3000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-3000/random_states_0.pkl +3 -0
- checkpoint-3000/scaler.pt +3 -0
- checkpoint-3000/scheduler.bin +3 -0
- checkpoint-3500/optimizer.bin +3 -0
- checkpoint-3500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-3500/random_states_0.pkl +3 -0
- checkpoint-3500/scaler.pt +3 -0
- checkpoint-3500/scheduler.bin +3 -0
- checkpoint-4000/optimizer.bin +3 -0
- checkpoint-4000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-4000/random_states_0.pkl +3 -0
- checkpoint-4000/scaler.pt +3 -0
- checkpoint-4000/scheduler.bin +3 -0
- checkpoint-4500/optimizer.bin +3 -0
- checkpoint-4500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-4500/random_states_0.pkl +3 -0
- checkpoint-4500/scaler.pt +3 -0
- checkpoint-4500/scheduler.bin +3 -0
- checkpoint-5000/optimizer.bin +3 -0
- checkpoint-5000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-5000/random_states_0.pkl +3 -0
- checkpoint-5000/scaler.pt +3 -0
- checkpoint-5000/scheduler.bin +3 -0
- hcwf-2500/optimizer.bin +3 -0
- hcwf-2500/pytorch_lora_weights.safetensors +3 -0
- hcwf-2500/random_states_0.pkl +3 -0
- hcwf-2500/scaler.pt +3 -0
- hcwf-2500/scheduler.bin +3 -0
- logs/dreambooth-sd3-lora/1734752690.5382943/events.out.tfevents.1734752690.aigpu08012.666434.1 +3 -0
- logs/dreambooth-sd3-lora/1734752690.5487766/hparams.yml +74 -0
- logs/dreambooth-sd3-lora/events.out.tfevents.1734752690.aigpu08012.666434.0 +3 -0
- pytorch_lora_weights.safetensors +3 -0
README.md
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---
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base_model: stabilityai/stable-diffusion-3.5-large
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library_name: diffusers
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license: other
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instance_prompt: jshj 3d ultrasound image of baby face, headshot
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widget: []
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tags:
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- text-to-image
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- diffusers-training
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- diffusers
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- lora
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- template:sd-lora
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- sd3.5-large
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- sd3.5
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- sd3.5-diffusers
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---
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<!-- This model card has been generated automatically according to the information the training script had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# SD3.5-Large DreamBooth LoRA - cwhuh/v4_sd35large_reconstruction
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<Gallery />
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## Model description
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These are cwhuh/v4_sd35large_reconstruction DreamBooth LoRA weights for stabilityai/stable-diffusion-3.5-large.
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The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [SD3 diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_sd3.md).
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Was LoRA for the text encoder enabled? False.
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## Trigger words
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You should use `jshj 3d ultrasound image of baby face, headshot` to trigger the image generation.
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## Download model
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[Download the *.safetensors LoRA](cwhuh/v4_sd35large_reconstruction/tree/main) in the Files & versions tab.
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## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
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```py
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from diffusers import AutoPipelineForText2Image
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import torch
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pipeline = AutoPipelineForText2Image.from_pretrained(stabilityai/stable-diffusion-3.5-large, torch_dtype=torch.float16).to('cuda')
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pipeline.load_lora_weights('cwhuh/v4_sd35large_reconstruction', weight_name='pytorch_lora_weights.safetensors')
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image = pipeline('jshj 3d ultrasound image of baby face, headshot').images[0]
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```
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### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
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- **LoRA**: download **[`diffusers_lora_weights.safetensors` here 💾](/cwhuh/v4_sd35large_reconstruction/blob/main/diffusers_lora_weights.safetensors)**.
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- Rename it and place it on your `models/Lora` folder.
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- On AUTOMATIC1111, load the LoRA by adding `<lora:your_new_name:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
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For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
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## License
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Please adhere to the licensing terms as described [here](https://huggingface.co/stabilityai/stable-diffusion-3.5-large/blob/main/LICENSE.md).
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## Intended uses & limitations
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#### How to use
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```python
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# TODO: add an example code snippet for running this diffusion pipeline
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```
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#### Limitations and bias
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[TODO: provide examples of latent issues and potential remediations]
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## Training details
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[TODO: describe the data used to train the model]
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
adam_beta1: 0.9
|
2 |
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adam_beta2: 0.999
|
3 |
+
adam_epsilon: 1.0e-08
|
4 |
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adam_weight_decay: 0.0001
|
5 |
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adam_weight_decay_text_encoder: 0.001
|
6 |
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allow_tf32: false
|
7 |
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cache_dir: /checkpoints/huggingface/
|
8 |
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cache_latents: false
|
9 |
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caption_column: null
|
10 |
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center_crop: false
|
11 |
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checkpointing_steps: 500
|
12 |
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checkpoints_total_limit: null
|
13 |
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class_data_dir: /code/chaewon/humanscape/data/ps1/truncated
|
14 |
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class_prompt: 3d ultrasound image of baby face, headshot
|
15 |
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dataloader_num_workers: 0
|
16 |
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dataset_config_name: null
|
17 |
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dataset_name: null
|
18 |
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gradient_accumulation_steps: 1
|
19 |
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gradient_checkpointing: true
|
20 |
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hub_model_id: null
|
21 |
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hub_token: null
|
22 |
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image_column: image
|
23 |
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instance_data_dir: /code/chaewon/humanscape/data/ps1/instance
|
24 |
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instance_prompt: jshj 3d ultrasound image of baby face, headshot
|
25 |
+
learning_rate: 1.0e-06
|
26 |
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local_rank: 0
|
27 |
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logging_dir: logs
|
28 |
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logit_mean: 0.0
|
29 |
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logit_std: 1.0
|
30 |
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lora_blocks: null
|
31 |
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lora_layers: null
|
32 |
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lr_num_cycles: 1
|
33 |
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lr_power: 1.0
|
34 |
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lr_scheduler: cosine_with_restarts
|
35 |
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lr_warmup_steps: 0
|
36 |
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max_grad_norm: 1.0
|
37 |
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max_sequence_length: 77
|
38 |
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max_train_steps: 5000
|
39 |
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mixed_precision: fp16
|
40 |
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mode_scale: 1.29
|
41 |
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num_class_images: 1000
|
42 |
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num_train_epochs: 10
|
43 |
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num_validation_images: 4
|
44 |
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optimizer: AdamW
|
45 |
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output_dir: v4_sd35large_reconstruction
|
46 |
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precondition_outputs: 1
|
47 |
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pretrained_model_name_or_path: stabilityai/stable-diffusion-3.5-large
|
48 |
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prior_generation_precision: null
|
49 |
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prior_loss_weight: 0.4
|
50 |
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prodigy_beta3: null
|
51 |
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prodigy_decouple: true
|
52 |
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prodigy_safeguard_warmup: true
|
53 |
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prodigy_use_bias_correction: true
|
54 |
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push_to_hub: true
|
55 |
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random_flip: false
|
56 |
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rank: 4
|
57 |
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repeats: 1
|
58 |
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report_to: tensorboard
|
59 |
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resolution: 512
|
60 |
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resume_from_checkpoint: hcwf-2500
|
61 |
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revision: null
|
62 |
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sample_batch_size: 4
|
63 |
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scale_lr: false
|
64 |
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seed: null
|
65 |
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text_encoder_lr: 5.0e-06
|
66 |
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train_batch_size: 1
|
67 |
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train_text_encoder: false
|
68 |
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upcast_before_saving: false
|
69 |
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use_8bit_adam: true
|
70 |
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validation_epochs: 50
|
71 |
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validation_prompt: null
|
72 |
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variant: null
|
73 |
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weighting_scheme: logit_normal
|
74 |
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with_prior_preservation: true
|
logs/dreambooth-sd3-lora/events.out.tfevents.1734752690.aigpu08012.666434.0
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:e347044a4a10a56998be664fd36d22956010d59ac3245bcaae4f4d3f5a7006bc
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size 210088
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pytorch_lora_weights.safetensors
ADDED
@@ -0,0 +1,3 @@
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1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:f17adfe13be23ec38a8cf7d4ce63a57b7cf0649eaca4a566b5eb7b05830dfbd9
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size 11868760
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