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End of training

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README.md ADDED
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+
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+ ---
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+ license: creativeml-openrail-m
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+ base_model: lambdalabs/miniSD-diffusers
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+ datasets:
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+ - kopyl/833-icons-dataset-1024-blip-large
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+ tags:
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+ - stable-diffusion
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+ - stable-diffusion-diffusers
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+ - text-to-image
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+ - diffusers
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+ inference: true
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+ ---
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+
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+ # Text-to-image finetuning - kopyl/nano-sd-tuned-sample
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+
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+ This pipeline was finetuned from **lambdalabs/miniSD-diffusers** on the **kopyl/833-icons-dataset-1024-blip-large** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['photo of a frog']:
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+
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+ ![val_imgs_grid](./val_imgs_grid.png)
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+
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+
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+ ## Pipeline usage
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+
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+ You can use the pipeline like so:
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+
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+ ```python
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+ from diffusers import DiffusionPipeline
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+ import torch
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+
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+ pipeline = DiffusionPipeline.from_pretrained("kopyl/nano-sd-tuned-sample", torch_dtype=torch.float16)
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+ prompt = "photo of a frog"
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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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+
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+ ## Training info
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+
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+ These are the key hyperparameters used during training:
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+
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+ * Epochs: 1
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+ * Learning rate: 1e-05
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+ * Batch size: 1
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+ * Gradient accumulation steps: 1
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+ * Image resolution: 256
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+ * Mixed-precision: fp16
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+
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+
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+ More information on all the CLI arguments and the environment are available on your [`wandb` run page](https://wandb.ai/spammmmm1997/text2image-fine-tune/runs/hs9vbf2e).
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+ }
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