End of training

.gitattributes

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README.md

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+---
+base_model: stabilityai/stable-diffusion-xl-base-1.0
+library_name: diffusers
+license: creativeml-openrail-m
+inference: true
+tags:
+- stable-diffusion-xl
+- stable-diffusion-xl-diffusers
+- text-to-image
+- diffusers-training
+- diffusers
+---
+
+<!-- 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. -->
+
+
+# Text-to-image finetuning - seungminh/ndxl_test
+
+This pipeline was finetuned from **stabilityai/stable-diffusion-xl-base-1.0** on the **seungminh/ndot_subset_random** dataset. Below are some example images generated with the finetuned pipeline using the following prompt: beautiful scenery nature glass bottle landscape, purple galaxy bottle: 
+
+![img_0](./image_0.png)
+![img_1](./image_1.png)
+![img_2](./image_2.png)
+![img_3](./image_3.png)
+
+
+Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
+
+
+## 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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model_index.json

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+  "_diffusers_version": "0.32.0.dev0",
+  "_name_or_path": "stabilityai/stable-diffusion-xl-base-1.0",
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+  "image_encoder": [
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+  "tokenizer_2": [
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+  ]
+}

scheduler/scheduler_config.json

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+  "interpolation_type": "linear",
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+  "prediction_type": "epsilon",
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+  "timestep_spacing": "leading",
+  "timestep_type": "discrete",
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+}

text_encoder/config.json

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+  "initializer_factor": 1.0,
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+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 77,
+  "model_type": "clip_text_model",
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+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
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+  "torch_dtype": "float16",
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+  "vocab_size": 49408
+}

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