End of training

.gitattributes

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README.md

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+---
+base_model: stabilityai/stable-diffusion-3-medium-diffusers
+library_name: diffusers
+license: openrail++
+tags:
+- text-to-image
+- diffusers-training
+- diffusers
+- sd3
+- sd3-diffusers
+- template:sd-lora
+instance_prompt: a photo of sks dog
+widget:
+- text: A photo of sks dog in a bucket
+  output:
+    url: image_0.png
+- text: A photo of sks dog in a bucket
+  output:
+    url: image_1.png
+- text: A photo of sks dog in a bucket
+  output:
+    url: image_2.png
+- text: A photo of sks dog in a bucket
+  output:
+    url: image_3.png
+---
+
+<!-- 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. -->
+
+
+# SD3 DreamBooth - feiyangyang/trained-sd3
+
+<Gallery />
+
+## Model description
+
+These are feiyangyang/trained-sd3 DreamBooth weights for stabilityai/stable-diffusion-3-medium-diffusers.
+
+The weights were trained using [DreamBooth](https://dreambooth.github.io/) with the [SD3 diffusers trainer](https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/README_sd3.md).
+
+Was the text encoder fine-tuned? False.
+
+## Trigger words
+
+You should use `a photo of sks dog` to trigger the image generation.
+
+## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
+
+```py
+from diffusers import AutoPipelineForText2Image
+import torch
+pipeline = AutoPipelineForText2Image.from_pretrained('feiyangyang/trained-sd3', torch_dtype=torch.float16).to('cuda')
+image = pipeline('A photo of sks dog in a bucket').images[0]
+```
+
+## License
+
+Please adhere to the licensing terms as described `[here](https://huggingface.co/stabilityai/stable-diffusion-3-medium/blob/main/LICENSE)`.
+
+
+## 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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+  "_diffusers_version": "0.30.0.dev0",
+  "_name_or_path": "stabilityai/stable-diffusion-3-medium-diffusers",
+  "attention_head_dim": 64,
+  "caption_projection_dim": 1536,
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+  "num_attention_heads": 24,
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+  "out_channels": 16,
+  "patch_size": 2,
+  "pooled_projection_dim": 2048,
+  "pos_embed_max_size": 192,
+  "sample_size": 128
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+  "vae": [
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+    "AutoencoderKL"
+  ]
+}

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