|
|
| --- |
| 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-3.0 |
| |
| 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']: |
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|  |
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|
|
| ## Pipeline usage |
|
|
| You can use the pipeline like so: |
|
|
| ```python |
| from diffusers import DiffusionPipeline |
| import torch |
| |
| pipeline = AutoPipelineForText2Image.from_pretrained("ChoudharyTAlhaArain/kadsinky-web-decoder-3.0", 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: 12 |
| * Learning rate: 1e-05 |
| * Batch size: 1 |
| * Gradient accumulation steps: 4 |
| * Image resolution: 512 |
| * Mixed-precision: None |
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|
|
| 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/4cxnthbk). |
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|
