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End of training

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  1. .gitattributes +4 -0
  2. README.md +47 -0
  3. checkpoint-100/optimizer.bin +3 -0
  4. checkpoint-100/pytorch_lora_weights.safetensors +3 -0
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.gitattributes CHANGED
@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ ---
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+ base_model: stabilityai/stable-diffusion-2
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+ library_name: diffusers
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+ license: creativeml-openrail-m
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+ inference: true
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+ instance_prompt: a photo of a dog
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+ tags:
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+ - text-to-image
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+ - diffusers
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+ - lora
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+ - diffusers-training
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+ - stable-diffusion
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+ - stable-diffusion-diffusers
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+ ---
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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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+
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+
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+ # LoRA DreamBooth - joortif/dogs-stable-diffusion-v2
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+
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+ These are LoRA adaption weights for stabilityai/stable-diffusion-2. The weights were trained on a photo of a dog using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following.
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+
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+ ![img_0](./image_0.png)
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+ ![img_1](./image_1.png)
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+ ![img_2](./image_2.png)
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+ ![img_3](./image_3.png)
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+
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+
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+ LoRA for the text encoder was enabled: False.
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+
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+
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+ ## Intended uses & limitations
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+
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+ #### How to use
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+
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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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+
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+ #### Limitations and bias
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+
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+ [TODO: provide examples of latent issues and potential remediations]
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+
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+ ## Training details
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+
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+ [TODO: describe the data used to train the model]
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+ adam_beta1: 0.9
2
+ adam_beta2: 0.999
3
+ adam_epsilon: 1.0e-08
4
+ adam_weight_decay: 0.01
5
+ allow_tf32: false
6
+ center_crop: false
7
+ checkpointing_steps: 100
8
+ checkpoints_total_limit: null
9
+ class_data_dir: null
10
+ class_labels_conditioning: null
11
+ class_prompt: null
12
+ dataloader_num_workers: 0
13
+ enable_xformers_memory_efficient_attention: false
14
+ gradient_accumulation_steps: 1
15
+ gradient_checkpointing: false
16
+ hub_model_id: joortif/dogs-stable-diffusion-v2
17
+ hub_token: null
18
+ instance_data_dir: dogs
19
+ instance_prompt: a photo of a dog
20
+ learning_rate: 0.0001
21
+ local_rank: -1
22
+ logging_dir: logs
23
+ lr_num_cycles: 1
24
+ lr_power: 1.0
25
+ lr_scheduler: constant
26
+ lr_warmup_steps: 0
27
+ max_grad_norm: 1.0
28
+ max_train_steps: 1000
29
+ mixed_precision: bf16
30
+ num_class_images: 100
31
+ num_train_epochs: 200
32
+ num_validation_images: 4
33
+ output_dir: dogs-stable-diffusion-v2
34
+ pre_compute_text_embeddings: false
35
+ pretrained_model_name_or_path: stabilityai/stable-diffusion-2
36
+ prior_generation_precision: null
37
+ prior_loss_weight: 1.0
38
+ push_to_hub: true
39
+ rank: 4
40
+ report_to: tensorboard
41
+ resolution: 768
42
+ resume_from_checkpoint: null
43
+ revision: null
44
+ sample_batch_size: 4
45
+ scale_lr: false
46
+ seed: 0
47
+ text_encoder_use_attention_mask: false
48
+ tokenizer_max_length: null
49
+ tokenizer_name: null
50
+ train_batch_size: 1
51
+ train_text_encoder: false
52
+ use_8bit_adam: false
53
+ validation_epochs: 50
54
+ validation_prompt: a photo of a dog with a racket playing tennis
55
+ variant: null
56
+ with_prior_preservation: false