End of training

.ipynb_checkpoints/README-checkpoint.md

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+---
+license: creativeml-openrail-m
+library_name: diffusers
+tags:
+- text-to-image
+- dreambooth
+- diffusers-training
+- stable-diffusion
+- stable-diffusion-diffusers
+- text-to-image
+- dreambooth
+- diffusers-training
+- stable-diffusion
+- stable-diffusion-diffusers
+base_model: stabilityai/stable-diffusion-2-1
+inference: true
+instance_prompt: a photo of [v]dog
+---
+
+<!-- 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. -->
+
+
+# DreamBooth - Yulaaa/dogbooth
+
+This is a dreambooth model derived from stabilityai/stable-diffusion-2-1. The weights were trained on a photo of [v]dog using [DreamBooth](https://dreambooth.github.io/).
+You can find some example images in the following. 
+
+
+
+DreamBooth 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]

.ipynb_checkpoints/model_index-checkpoint.json

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+{
+  "_class_name": "StableDiffusionPipeline",
+  "_diffusers_version": "0.28.0.dev0",
+  "_name_or_path": "stabilityai/stable-diffusion-2-1",
+  "feature_extractor": [
+    "transformers",
+    "CLIPImageProcessor"
+  ],
+  "image_encoder": [
+    null,
+    null
+  ],
+  "requires_safety_checker": false,
+  "safety_checker": [
+    null,
+    null
+  ],
+  "scheduler": [
+    "diffusers",
+    "DDIMScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

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