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End of training

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README.md CHANGED
@@ -14,7 +14,7 @@ inference: true
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  # Text-to-image finetuning - iamkaikai/amazing-logos
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- This pipeline was finetuned from **runwayml/stable-diffusion-v1-5** on the **iamkaikai/amazing_logos_v2** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['Simple elegant logo for Digital Art, D A triangle Symmetrical, successful vibe, minimalist, thought-provoking, abstract, recognizable, black and white']:
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  ![val_imgs_grid](./val_imgs_grid.png)
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@@ -28,7 +28,7 @@ from diffusers import DiffusionPipeline
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  import torch
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  pipeline = DiffusionPipeline.from_pretrained("iamkaikai/amazing-logos", torch_dtype=torch.float16)
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- prompt = "Simple elegant logo for Digital Art, D A triangle Symmetrical, successful vibe, minimalist, thought-provoking, abstract, recognizable, black and white"
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  image = pipeline(prompt).images[0]
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  image.save("my_image.png")
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  ```
@@ -37,7 +37,7 @@ image.save("my_image.png")
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  These are the key hyperparameters used during training:
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- * Epochs: 17
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  * Learning rate: 1e-07
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  * Batch size: 1
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  * Gradient accumulation steps: 1
@@ -45,4 +45,4 @@ These are the key hyperparameters used during training:
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  * Mixed-precision: fp16
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- More information on all the CLI arguments and the environment are available on your [`wandb` run page](https://wandb.ai/iam-kai-kai/text2image-fine-tune/runs/o936ikb3).
 
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  # Text-to-image finetuning - iamkaikai/amazing-logos
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+ This pipeline was finetuned from **runwayml/stable-diffusion-v1-5** on the **iamkaikai/amazing_logos_v2** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['Simple elegant logo for Digital Art, D A Square Symmetrical, successful vibe, minimalist, thought-provoking, abstract, recognizable, black and white']:
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  ![val_imgs_grid](./val_imgs_grid.png)
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  import torch
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  pipeline = DiffusionPipeline.from_pretrained("iamkaikai/amazing-logos", torch_dtype=torch.float16)
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+ prompt = "Simple elegant logo for Digital Art, D A Square Symmetrical, successful vibe, minimalist, thought-provoking, abstract, recognizable, black and white"
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  image = pipeline(prompt).images[0]
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  image.save("my_image.png")
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  ```
 
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  These are the key hyperparameters used during training:
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+ * Epochs: 20
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  * Learning rate: 1e-07
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  * Batch size: 1
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  * Gradient accumulation steps: 1
 
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  * Mixed-precision: fp16
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+ More information on all the CLI arguments and the environment are available on your [`wandb` run page](https://wandb.ai/iam-kai-kai/text2image-fine-tune/runs/36y6uxai).
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