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Update app.py
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app.py
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@@ -9,7 +9,7 @@ from huggingface_hub import upload_file
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import json
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from uuid import uuid4
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import logging
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logging.basicConfig(filename="logs.log", filemode='a', format='%(asctime)s %(message)s'
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logger = logging.getLogger()
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@@ -107,7 +107,7 @@ ci = gr.ChatInterface(
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# ("The model will become slow" is bc this uncaches the prompt and prompt processing is a big part of the generation time)
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gr.Slider(minimum=0.0, maximum=1.0, value=0.1, step=0.01, label="Min_p", info="Lower values give it more \"personality\""),
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gr.Slider(minimum=0.1, maximum=4.0, value=1.5, step=0.1, label="Temperature", info="How chaotic should the model be?"),
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gr.Slider(minimum=0, maximum=512, value=
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gr.Slider(minimum=0.5, maximum=1.5, value=1.015, step=0.001, label="Length penalty decay factor", info='How fast should that stop likelihood increase?'),
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gr.Slider(minimum=0.0, maximum=1.0, value=0.1, step=0.01, label="Frequency penalty", info='"Don\'repeat yourself"'),
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gr.Slider(minimum=0.0, maximum=1.0, value=0.1, step=0.01, label="Presence penalty", info='"Use lots of diverse words"'),
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import json
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from uuid import uuid4
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import logging
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logging.basicConfig(filename="logs.log", filemode='a', format='%(asctime)s %(message)s')
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logger = logging.getLogger()
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# ("The model will become slow" is bc this uncaches the prompt and prompt processing is a big part of the generation time)
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gr.Slider(minimum=0.0, maximum=1.0, value=0.1, step=0.01, label="Min_p", info="Lower values give it more \"personality\""),
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gr.Slider(minimum=0.1, maximum=4.0, value=1.5, step=0.1, label="Temperature", info="How chaotic should the model be?"),
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gr.Slider(minimum=0, maximum=512, value=64, step=1, label="Length penalty start", info='When should the model start being more likely to shut up?'),
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gr.Slider(minimum=0.5, maximum=1.5, value=1.015, step=0.001, label="Length penalty decay factor", info='How fast should that stop likelihood increase?'),
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gr.Slider(minimum=0.0, maximum=1.0, value=0.1, step=0.01, label="Frequency penalty", info='"Don\'repeat yourself"'),
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gr.Slider(minimum=0.0, maximum=1.0, value=0.1, step=0.01, label="Presence penalty", info='"Use lots of diverse words"'),
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