|
|
| --- |
| license: creativeml-openrail-m |
| base_model: kandinsky-community/kandinsky-2-2-prior |
| datasets: |
| - kbharat7/DogChestXrayDatasetNew |
| tags: |
| - kandinsky |
| - text-to-image |
| - diffusers |
| - diffusers-training |
| inference: true |
| --- |
| |
| # Finetuning - aditya11997/test_prior |
| |
| This pipeline was finetuned from **kandinsky-community/kandinsky-2-2-prior** on the **kbharat7/DogChestXrayDatasetNew** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['dogxraysmall']: |
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|  |
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| ## Pipeline usage |
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| You can use the pipeline like so: |
|
|
| ```python |
| from diffusers import DiffusionPipeline |
| import torch |
| |
| pipe_prior = DiffusionPipeline.from_pretrained("aditya11997/test_prior", torch_dtype=torch.float16) |
| pipe_t2i = DiffusionPipeline.from_pretrained("kandinsky-community/kandinsky-2-2-decoder", torch_dtype=torch.float16) |
| prompt = "dogxraysmall" |
| image_embeds, negative_image_embeds = pipe_prior(prompt, guidance_scale=1.0).to_tuple() |
| image = pipe_t2i(image_embeds=image_embeds, negative_image_embeds=negative_image_embeds).images[0] |
| image.save("my_image.png") |
| ``` |
|
|
| ## Training info |
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| These are the key hyperparameters used during training: |
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| * Epochs: 1 |
| * Learning rate: 1e-05 |
| * Batch size: 1 |
| * Gradient accumulation steps: 4 |
| * Image resolution: 768 |
| * 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/aditya11997/text2image-fine-tune/runs/9j7m0fr8). |
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