Upload fusion_t2i_CLIP_interrogator.ipynb
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Google Colab Notebooks/fusion_t2i_CLIP_interrogator.ipynb
CHANGED
@@ -52,7 +52,7 @@
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" for symbol in ['^']:\n",
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" result = result.replace(symbol,'')\n",
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" #------#\n",
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" result = result.replace('\\\\|','|')\n",
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" return result;\n",
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"\n",
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"\n",
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@@ -429,9 +429,9 @@
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"newline_Separator = False # param {type:\"boolean\"}\n",
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"\n",
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"import random\n",
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"list_size2 =
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"start_at_index2 =
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"rate_percent =
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"\n",
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"# @markdown Repeat output N times\n",
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"N = 7 # @param {type:\"slider\", min:0, max:10, step:1}\n",
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@@ -537,7 +537,7 @@
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"\n",
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" # title Show the 100 most similiar suffix and prefix text-encodings to the text encoding\n",
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" RANGE = list_size\n",
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" separator = '|'\n",
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" if newline_Separator : separator = separator + '\\n'\n",
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"\n",
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" _prompts = ''\n",
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" for symbol in ['^']:\n",
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" result = result.replace(symbol,'')\n",
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" #------#\n",
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" result = result.replace('\\\\|','|').replace(' |',' |')\n",
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" return result;\n",
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"\n",
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"\n",
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"newline_Separator = False # param {type:\"boolean\"}\n",
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"\n",
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"import random\n",
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"list_size2 = 0 # param {type:'number'}\n",
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"start_at_index2 = NUM_VOCAB_ITEMS # param {type:'number'}\n",
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"rate_percent = -1 # param {type:\"slider\", min:0, max:100, step:1}\n",
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"\n",
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"# @markdown Repeat output N times\n",
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"N = 7 # @param {type:\"slider\", min:0, max:10, step:1}\n",
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"\n",
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" # title Show the 100 most similiar suffix and prefix text-encodings to the text encoding\n",
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" RANGE = list_size\n",
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" separator = ' |'\n",
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" if newline_Separator : separator = separator + '\\n'\n",
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"\n",
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" _prompts = ''\n",
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