End of training

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+base_model: HiDream-ai/HiDream-I1-Full
+library_name: diffusers
+license: mit
+instance_prompt: a dog, yarn art style
+widget:
+- text: yoda, yarn art style
+  output:
+    url: image_0.png
+- text: yoda, yarn art style
+  output:
+    url: image_1.png
+- text: yoda, yarn art style
+  output:
+    url: image_2.png
+- text: yoda, yarn art style
+  output:
+    url: image_3.png
+tags:
+- text-to-image
+- diffusers-training
+- diffusers
+- lora
+- hidream
+- hidream-diffusers
+- template:sd-lora
+---
+
+<!-- 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. -->
+
+
+# HiDream Image DreamBooth LoRA - linoyts/hidream-yarn-art-lora-v2-trainer-multi
+
+<Gallery />
+
+## Model description
+
+These are linoyts/hidream-yarn-art-lora-v2-trainer-multi DreamBooth LoRA weights for HiDream-ai/HiDream-I1-Full.
+
+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).
+
+## Trigger words
+
+You should use `a dog, yarn art style` to trigger the image generation.
+
+## Download model
+
+[Download the *.safetensors LoRA](linoyts/hidream-yarn-art-lora-v2-trainer-multi/tree/main) in the Files & versions tab.
+
+## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
+
+```py
+    >>> import torch
+    >>> from transformers import PreTrainedTokenizerFast, LlamaForCausalLM
+    >>> from diffusers import HiDreamImagePipeline
+
+    >>> tokenizer_4 = PreTrainedTokenizerFast.from_pretrained("meta-llama/Meta-Llama-3.1-8B-Instruct")
+    >>> text_encoder_4 = LlamaForCausalLM.from_pretrained(
+    ...     "meta-llama/Meta-Llama-3.1-8B-Instruct",
+    ...     output_hidden_states=True,
+    ...     output_attentions=True,
+    ...     torch_dtype=torch.bfloat16,
+    ... )
+
+    >>> pipe = HiDreamImagePipeline.from_pretrained(
+    ...     "HiDream-ai/HiDream-I1-Full",
+    ...     tokenizer_4=tokenizer_4,
+    ...     text_encoder_4=text_encoder_4,
+    ...     torch_dtype=torch.bfloat16,
+    ... )
+    >>> pipe.enable_model_cpu_offload()
+    >>> pipe.load_lora_weights(f"linoyts/hidream-yarn-art-lora-v2-trainer-multi")
+    >>> image = pipe(f"a dog, yarn art style").images[0]
+
+
+```
+
+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)
+
+
+## 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]

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