End of training

README.md

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+
+---
+license: creativeml-openrail-m
+base_model: kandinsky-community/kandinsky-2-2-decoder
+datasets:
+- ChoudharyTAlhaArain/web-kadi-2.0
+prior:
+- kandinsky-community/kandinsky-2-2-prior
+tags:
+- kandinsky
+- text-to-image
+- diffusers
+- diffusers-training
+inference: true
+---
+    
+# Finetuning - ChoudharyTAlhaArain/kadsinky-web-decoder-3.1
+
+This pipeline was finetuned from **kandinsky-community/kandinsky-2-2-decoder** on the **ChoudharyTAlhaArain/web-kadi-2.0** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['update web ui/ux']: 
+
+![val_imgs_grid](./val_imgs_grid.png)
+
+
+## Pipeline usage
+
+You can use the pipeline like so:
+
+```python
+from diffusers import DiffusionPipeline
+import torch
+
+pipeline = AutoPipelineForText2Image.from_pretrained("ChoudharyTAlhaArain/kadsinky-web-decoder-3.1", torch_dtype=torch.float16)
+prompt = "update web ui/ux"
+image = pipeline(prompt).images[0]
+image.save("my_image.png")
+```
+
+## Training info
+
+These are the key hyperparameters used during training:
+
+* Epochs: 116
+* Learning rate: 1e-05
+* Batch size: 1
+* Gradient accumulation steps: 4
+* Image resolution: 512
+* Mixed-precision: None
+
+
+More information on all the CLI arguments and the environment are available on your [`wandb` run page](https://wandb.ai/tanveer-talha-github/text2image-fine-tune/runs/u24l8tl8).

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+  "_diffusers_version": "0.31.0.dev0",
+  "_name_or_path": "kandinsky-community/kandinsky-2-2-decoder",
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+    "SimpleCrossAttnDownBlock2D",
+    "SimpleCrossAttnDownBlock2D",
+    "SimpleCrossAttnDownBlock2D"
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