End of training

.gitattributes

@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+image_0.png filter=lfs diff=lfs merge=lfs -text
+image_1.png filter=lfs diff=lfs merge=lfs -text
+image_2.png filter=lfs diff=lfs merge=lfs -text
+image_3.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,45 @@
+---
+base_model: Lykon/dreamshaper-xl-v2-turbo
+library_name: diffusers
+license: creativeml-openrail-m
+tags:
+- stable-diffusion-xl
+- stable-diffusion-xl-diffusers
+- text-to-image
+- diffusers-training
+- diffusers
+inference: true
+---
+
+<!-- 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 - almarinastudio/trained_sdxl40
+
+This pipeline was finetuned from **Lykon/dreamshaper-xl-v2-turbo** on the **almarinastudio/dataset28** dataset. Below are some example images generated with the finetuned pipeline using the following prompt: A young male playing basketball on the school stadium in the morning.: 
+
+![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]

model_index.json

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+  "_diffusers_version": "0.30.0",
+  "_name_or_path": "Lykon/dreamshaper-xl-v2-turbo",
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+  ],
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+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

scheduler/scheduler_config.json

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+  "prediction_type": "epsilon",
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+  "use_karras_sigmas": false
+}

text_encoder/config.json

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+  "model_type": "clip_text_model",
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+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "projection_dim": 768,
+  "torch_dtype": "float16",
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tokenizer/special_tokens_map.json

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