ProGamerGov
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Better training description
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README.md
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@@ -10,15 +10,15 @@ The embeddings in this repository were trained for the 768px [Stable Diffusion v
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**Knollingcase v1**
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The v1 embeddings were trained for 4000 iterations with a batch size of 2, a text dropout of 10%, & 16 vectors using Automatic1111's WebUI. A total of 69 training images were used.
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**Knollingcase v2**
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The v2 embeddings were trained for 5000 iterations with a batch size of 4 and a text dropout of 10%, & 16 vectors using Automatic1111's WebUI. A total of 78 training images were used.
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**Knollingcase v3**
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The v3 embeddings were trained for 4000-6250 iterations with a batch size of 4 and a text dropout of 10%, & 16 vectors using Automatic1111's WebUI. A total of 86 training images were used.
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<div align="center">
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<img src="https://huggingface.co/ProGamerGov/knollingcase-embeddings-sd-v2-0/resolve/main/cruise_ship_on_wave_kc16-v3-6250.png">
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@@ -29,7 +29,7 @@ The v3 embeddings were trained for 4000-6250 iterations with a batch size of 4 a
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**Knollingcase v4**
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The v4 embeddings were trained for 4000-6250 iterations with a batch size of 4 and a text dropout of 10%, using Automatic1111's WebUI. A total of 116 training images were used.
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To use the embeddings, download and then rename the file to whatever trigger word you want to use.
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**Knollingcase v1**
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The v1 embeddings were trained for 4000 iterations with a batch size of 2, a text dropout of 10%, & 16 vectors using Automatic1111's WebUI. A total of 69 training images with high quality captions were used.
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**Knollingcase v2**
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The v2 embeddings were trained for 5000 iterations with a batch size of 4 and a text dropout of 10%, & 16 vectors using Automatic1111's WebUI. A total of 78 training images with high quality captions were used.
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**Knollingcase v3**
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The v3 embeddings were trained for 4000-6250 iterations with a batch size of 4 and a text dropout of 10%, & 16 vectors using Automatic1111's WebUI. A total of 86 training images with high quality captions were used.
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<div align="center">
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<img src="https://huggingface.co/ProGamerGov/knollingcase-embeddings-sd-v2-0/resolve/main/cruise_ship_on_wave_kc16-v3-6250.png">
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**Knollingcase v4**
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The v4 embeddings were trained for 4000-6250 iterations with a batch size of 4 and a text dropout of 10%, using Automatic1111's WebUI. A total of 116 training images with high quality captions were used.
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To use the embeddings, download and then rename the file to whatever trigger word you want to use.
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