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End of training

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.gitattributes CHANGED
@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ base_model: HiDream-ai/HiDream-I1-Dev
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+ library_name: diffusers
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+ license: mit
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+ instance_prompt: 3d icon
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+ widget:
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+ - text: a 3dicon, a llama eating ramen
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+ output:
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+ url: image_0.png
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+ - text: a 3dicon, a llama eating ramen
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+ output:
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+ url: image_1.png
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+ - text: a 3dicon, a llama eating ramen
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+ output:
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+ url: image_2.png
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+ - text: a 3dicon, a llama eating ramen
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+ output:
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+ url: image_3.png
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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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+ - hidream
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+ - hidream-diffusers
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+ - template:sd-lora
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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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+ # HiDream Image DreamBooth LoRA - Nomnoos/trained-hidream-lora
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+
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+ <Gallery />
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+
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+ ## Model description
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+
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+ These are Nomnoos/trained-hidream-lora DreamBooth LoRA weights for HiDream-ai/HiDream-I1-Dev.
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+
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+ The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [HiDream Image diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_hidream.md).
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+
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+ ## Trigger words
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+
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+ You should use `3d icon` to trigger the image generation.
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+
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+ ## Download model
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+
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+ [Download the *.safetensors LoRA](Nomnoos/trained-hidream-lora/tree/main) in the Files & versions tab.
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+
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+ ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
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+
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+ ```py
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+ >>> import torch
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+ >>> from transformers import PreTrainedTokenizerFast, LlamaForCausalLM
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+ >>> from diffusers import HiDreamImagePipeline
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+
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+ >>> tokenizer_4 = PreTrainedTokenizerFast.from_pretrained("meta-llama/Meta-Llama-3.1-8B-Instruct")
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+ >>> text_encoder_4 = LlamaForCausalLM.from_pretrained(
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+ ... "meta-llama/Meta-Llama-3.1-8B-Instruct",
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+ ... output_hidden_states=True,
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+ ... output_attentions=True,
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+ ... torch_dtype=torch.bfloat16,
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+ ... )
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+
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+ >>> pipe = HiDreamImagePipeline.from_pretrained(
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+ ... "HiDream-ai/HiDream-I1-Full",
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+ ... tokenizer_4=tokenizer_4,
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+ ... text_encoder_4=text_encoder_4,
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+ ... torch_dtype=torch.bfloat16,
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+ ... )
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+ >>> pipe.enable_model_cpu_offload()
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+ >>> pipe.load_lora_weights(f"Nomnoos/trained-hidream-lora")
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+ >>> image = pipe(f"3d icon").images[0]
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+
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+
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+ ```
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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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+
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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
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+ adam_beta2: 0.999
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+ adam_epsilon: 1.0e-08
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+ adam_weight_decay: 0.0001
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+ allow_tf32: false
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+ bnb_quantization_config_path: null
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+ logging_dir: logs
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+ logit_mean: 0.0
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+ logit_std: 1.0
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+ lora_dropout: 0.0
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+ lora_layers: null
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+ lr_num_cycles: 1
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+ lr_power: 1.0
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+ lr_scheduler: constant_with_warmup
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+ lr_warmup_steps: 100
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+ max_grad_norm: 1.0
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+ max_sequence_length: 128
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+ max_train_steps: 1000
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+ mixed_precision: bf16
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+ mode_scale: 1.29
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+ num_class_images: 100
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+ num_train_epochs: 167
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+ num_validation_images: 4
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+ offload: false
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+ optimizer: AdamW
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+ output_dir: trained-hidream-lora
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+ pretrained_model_name_or_path: HiDream-ai/HiDream-I1-Dev
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+ pretrained_text_encoder_4_name_or_path: meta-llama/Meta-Llama-3.1-8B-Instruct
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+ resolution: 1024
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+ sample_batch_size: 4
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+ upcast_before_saving: false
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+ validation_epochs: 25
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+ validation_prompt: a 3dicon, a llama eating ramen
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+ weighting_scheme: none
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+ max_train_steps: 200
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+ mode_scale: 1.29
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+ num_class_images: 100
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+ num_train_epochs: 9
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+ num_validation_images: 4
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+ optimizer: AdamW
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+ output_dir: trained-hidream-lora
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+ pretrained_model_name_or_path: HiDream-ai/HiDream-I1-Dev
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+ pretrained_text_encoder_4_name_or_path: meta-llama/Meta-Llama-3.1-8B-Instruct
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+ pretrained_tokenizer_4_name_or_path: meta-llama/Meta-Llama-3.1-8B-Instruct
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