End of training

README.md

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+---
+base_model: runwayml/stable-diffusion-v1-5
+library_name: diffusers
+license: creativeml-openrail-m
+tags:
+- text-to-image
+- diffusers
+- lora
+- diffusers-training
+- stable-diffusion
+- stable-diffusion-diffusers
+inference: true
+instance_prompt: I want to eat  bread
+---
+
+<!-- This model card has been generated automatically according to the information the training script had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+
+# LoRA DreamBooth - codeiceman/bread-model
+
+These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on I want to eat  bread using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following. 
+
+![img_0](./image_0.png)
+![img_1](./image_1.png)
+![img_2](./image_2.png)
+![img_3](./image_3.png)
+
+
+LoRA for the text encoder was enabled: False.
+
+
+## Intended uses & limitations
+
+#### How to use
+
+```python
+# TODO: add an example code snippet for running this diffusion pipeline
+```
+
+#### Limitations and bias
+
+[TODO: provide examples of latent issues and potential remediations]
+
+## Training details
+
+[TODO: describe the data used to train the model]

logs/dreambooth-lora/1722996357.6893418/events.out.tfevents.1722996357.6fec217efaa8.729227.1

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logs/dreambooth-lora/1722996357.6906276/hparams.yml

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+adam_beta1: 0.9
+adam_beta2: 0.999
+adam_epsilon: 1.0e-08
+adam_weight_decay: 0.01
+allow_tf32: false
+center_crop: false
+checkpointing_steps: 100
+checkpoints_total_limit: null
+class_data_dir: null
+class_labels_conditioning: null
+class_prompt: null
+dataloader_num_workers: 0
+enable_xformers_memory_efficient_attention: false
+gradient_accumulation_steps: 1
+gradient_checkpointing: false
+hub_model_id: null
+hub_token: null
+instance_data_dir: bread
+instance_prompt: I want to eat  bread
+learning_rate: 0.0001
+local_rank: -1
+logging_dir: logs
+lr_num_cycles: 1
+lr_power: 1.0
+lr_scheduler: constant
+lr_warmup_steps: 0
+max_grad_norm: 1.0
+max_train_steps: 10
+mixed_precision: null
+num_class_images: 100
+num_train_epochs: 1
+num_validation_images: 4
+output_dir: bread-model
+pre_compute_text_embeddings: false
+pretrained_model_name_or_path: runwayml/stable-diffusion-v1-5
+prior_generation_precision: null
+prior_loss_weight: 1.0
+push_to_hub: true
+rank: 4
+report_to: tensorboard
+resolution: 512
+resume_from_checkpoint: null
+revision: null
+sample_batch_size: 4
+scale_lr: false
+seed: 0
+text_encoder_use_attention_mask: false
+tokenizer_max_length: null
+tokenizer_name: null
+train_batch_size: 1
+train_text_encoder: false
+use_8bit_adam: false
+validation_epochs: 50
+validation_prompt: I want to have bread
+variant: null
+with_prior_preservation: false

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pytorch_lora_weights.safetensors

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