End of training
Browse files- .gitattributes +4 -0
- README.md +96 -0
- image_0.png +3 -0
- image_1.png +3 -0
- image_2.png +3 -0
- image_3.png +3 -0
- logs/dreambooth-lora-sd-xl/1716938838.3230867/events.out.tfevents.1716938838.cookey39-osagav1ul6md-main.658.1 +3 -0
- logs/dreambooth-lora-sd-xl/1716938838.3255281/hparams.yml +80 -0
- logs/dreambooth-lora-sd-xl/events.out.tfevents.1716938838.cookey39-osagav1ul6md-main.658.0 +3 -0
- pytorch_lora_weights.safetensors +3 -0
- teratera.safetensors +3 -0
- teratera_emb.safetensors +3 -0
.gitattributes
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@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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image_0.png filter=lfs diff=lfs merge=lfs -text
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image_1.png filter=lfs diff=lfs merge=lfs -text
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image_2.png filter=lfs diff=lfs merge=lfs -text
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image_3.png filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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tags:
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- stable-diffusion-xl
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- stable-diffusion-xl-diffusers
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- diffusers-training
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- text-to-image
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- diffusers
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- lora
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- template:sd-lora
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widget:
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- text: 'In the style of Terada,colorful, anime-style, illustration, girl, yellow jacket, blonde hair, two buns, peace sign, hands, rainbow gradient, brightness, cheerfulness, small confetti, festive atmosphere, central position, joy, positivity.'
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output:
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url:
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"image_0.png"
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- text: 'In the style of Terada,colorful, anime-style, illustration, girl, yellow jacket, blonde hair, two buns, peace sign, hands, rainbow gradient, brightness, cheerfulness, small confetti, festive atmosphere, central position, joy, positivity.'
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output:
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url:
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"image_1.png"
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- text: 'In the style of Terada,colorful, anime-style, illustration, girl, yellow jacket, blonde hair, two buns, peace sign, hands, rainbow gradient, brightness, cheerfulness, small confetti, festive atmosphere, central position, joy, positivity.'
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output:
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url:
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"image_2.png"
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- text: 'In the style of Terada,colorful, anime-style, illustration, girl, yellow jacket, blonde hair, two buns, peace sign, hands, rainbow gradient, brightness, cheerfulness, small confetti, festive atmosphere, central position, joy, positivity.'
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output:
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url:
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"image_3.png"
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base_model: cookey39/aam_xl
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instance_prompt: In the style of Terada,
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license: openrail++
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---
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# SDXL LoRA DreamBooth - cookey39/teratera
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<Gallery />
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## Model description
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### These are cookey39/teratera LoRA adaption weights for cookey39/aam_xl.
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## Download model
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### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke
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- **LoRA**: download **[`teratera.safetensors` here 💾](/cookey39/teratera/blob/main/teratera.safetensors)**.
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- Place it on your `models/Lora` folder.
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- On AUTOMATIC1111, load the LoRA by adding `<lora:teratera:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
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- *Embeddings*: download **[`teratera_emb.safetensors` here 💾](/cookey39/teratera/blob/main/teratera_emb.safetensors)**.
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- Place it on it on your `embeddings` folder
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- Use it by adding `teratera_emb` to your prompt. For example, `In the style of Terada,`
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(you need both the LoRA and the embeddings as they were trained together for this LoRA)
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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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from huggingface_hub import hf_hub_download
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from safetensors.torch import load_file
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pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
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pipeline.load_lora_weights('cookey39/teratera', weight_name='pytorch_lora_weights.safetensors')
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embedding_path = hf_hub_download(repo_id='cookey39/teratera', filename='teratera_emb.safetensors', repo_type="model")
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state_dict = load_file(embedding_path)
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pipeline.load_textual_inversion(state_dict["clip_l"], token=[], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer)
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pipeline.load_textual_inversion(state_dict["clip_g"], token=[], text_encoder=pipeline.text_encoder_2, tokenizer=pipeline.tokenizer_2)
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image = pipeline('In the style of Terada,colorful, anime-style, illustration, girl, yellow jacket, blonde hair, two buns, peace sign, hands, rainbow gradient, brightness, cheerfulness, small confetti, festive atmosphere, central position, joy, positivity.').images[0]
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```
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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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## Trigger words
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To trigger image generation of trained concept(or concepts) replace each concept identifier in you prompt with the new inserted tokens:
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to trigger concept `TOK` → use `<s0><s1>` in your prompt
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## Details
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All [Files & versions](/cookey39/teratera/tree/main).
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The weights were trained using [🧨 diffusers Advanced Dreambooth Training Script](https://github.com/huggingface/diffusers/blob/main/examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py).
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LoRA for the text encoder was enabled. False.
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Pivotal tuning was enabled: True.
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Special VAE used for training: None.
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image_0.png
ADDED
Git LFS Details
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image_1.png
ADDED
Git LFS Details
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image_2.png
ADDED
Git LFS Details
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image_3.png
ADDED
Git LFS Details
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logs/dreambooth-lora-sd-xl/1716938838.3230867/events.out.tfevents.1716938838.cookey39-osagav1ul6md-main.658.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:94f54fcf275b5bee29835a1b6cd71d5619b29add2ac75fceb5c6a3f112fbe5af
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size 3792
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logs/dreambooth-lora-sd-xl/1716938838.3255281/hparams.yml
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adam_beta1: 0.9
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adam_beta2: 0.99
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adam_epsilon: 1.0e-08
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adam_weight_decay: 0.0001
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adam_weight_decay_text_encoder: null
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allow_tf32: false
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cache_dir: null
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cache_latents: false
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caption_column: prompt
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center_crop: false
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checkpointing_steps: 2000
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checkpoints_total_limit: null
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class_data_dir: null
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class_prompt: null
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dataloader_num_workers: 0
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dataset_config_name: null
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dataset_name: /openbayes/home/img
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do_edm_style_training: false
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enable_xformers_memory_efficient_attention: false
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gradient_accumulation_steps: 1
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gradient_checkpointing: true
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hub_model_id: null
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hub_token: null
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image_column: image
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instance_data_dir: null
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instance_prompt: In the style of Terada,
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learning_rate: 1.0
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local_rank: -1
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logging_dir: logs
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lora_unet_blocks: null
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lr_num_cycles: 1
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lr_power: 1.0
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lr_scheduler: constant
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lr_warmup_steps: 0
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max_grad_norm: 1.0
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max_train_steps: 1000
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mixed_precision: bf16
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noise_offset: 0
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num_class_images: 100
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num_new_tokens_per_abstraction: 2
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num_train_epochs: 143
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num_validation_images: 4
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optimizer: prodigy
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output_dir: teratera
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pretrained_model_name_or_path: cookey39/aam_xl
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pretrained_vae_model_name_or_path: null
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prior_generation_precision: null
|
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prior_loss_weight: 1.0
|
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+
prodigy_beta3: null
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prodigy_decouple: true
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prodigy_safeguard_warmup: true
|
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prodigy_use_bias_correction: true
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push_to_hub: true
|
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+
random_flip: false
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rank: 8
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repeats: 1
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report_to: tensorboard
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resolution: 1024
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resume_from_checkpoint: null
|
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revision: null
|
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sample_batch_size: 4
|
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scale_lr: false
|
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seed: 0
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snr_gamma: 5.0
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text_encoder_lr: 1.0
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token_abstraction: TOK
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train_batch_size: 3
|
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train_text_encoder: false
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train_text_encoder_frac: 1.0
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train_text_encoder_ti: true
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train_text_encoder_ti_frac: 0.5
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use_8bit_adam: false
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use_blora: false
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use_dora: false
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validation_epochs: 50
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validation_prompt: In the style of Terada,colorful, anime-style, illustration, girl,
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yellow jacket, blonde hair, two buns, peace sign, hands, rainbow gradient, brightness,
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cheerfulness, small confetti, festive atmosphere, central position, joy, positivity.
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variant: null
|
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with_prior_preservation: false
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logs/dreambooth-lora-sd-xl/events.out.tfevents.1716938838.cookey39-osagav1ul6md-main.658.0
ADDED
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pytorch_lora_weights.safetensors
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teratera.safetensors
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teratera_emb.safetensors
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