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https://github.com/KoboldAI/KoboldAI-Client.git
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90bc99f0e5
Add convert script for making official.presets files from excel files maintained by LightSaveUs
60 lines
2.8 KiB
Python
60 lines
2.8 KiB
Python
import pandas as pd
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import sys
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output = []
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sheet_mapper = {"KAI-ADAPTED 13B": "13B", "KAI-ADAPTED 6B": "6B", 'KAI-CUSTOM': 'Custom'}
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for file in ['KoboldAI Settings (6B).xlsx', 'KoboldAI Settings (13B).xlsx', 'KoboldAI Settings (Custom).xlsx', 'KoboldAI Settings (Original).xlsx']:
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presets = pd.read_excel("preset Files/{}".format(file), None)
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for sheet in presets:
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df = presets[sheet]
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if sheet in sheet_mapper:
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sheet = sheet_mapper[sheet]
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df = df.dropna(axis=1, how='all')
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df = df.rename(columns={"Unnamed: 0": "setting"})
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df = pd.melt(df, id_vars=['setting'])
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df = df.rename(columns={"variable": "preset"})
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df['fix'] = df['value'].str.replace(" (KAI)", "", regex=False)
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df.loc[~df['fix'].isnull(), 'value'] = df['fix']
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df = df.drop(columns=['fix'])
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df.loc[df['setting']=='Samplers Order', 'value'] = df['value'].str.replace("Temp", "5", regex=False)
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df.loc[df['setting']=='Samplers Order', 'value'] = df['value'].str.replace("K", "0", regex=False)
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df.loc[df['setting']=='Samplers Order', 'value'] = df['value'].str.replace("TFS", "3", regex=False)
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df.loc[df['setting']=='Samplers Order', 'value'] = df['value'].str.replace("A", "1", regex=False)
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df.loc[df['setting']=='Samplers Order', 'value'] = df['value'].str.replace("Typ", "4", regex=False)
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df.loc[df['setting']=='Samplers Order', 'value'] = df['value'].str.replace("P", "2", regex=False)
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settings_mapper = {'Temperature': 'temp', 'Output Length': 'genamt', 'Repetition Penalty': 'rep_pen',
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'Top P': 'top_p', 'Top K': 'top_k', 'Tail-Free': 'tfs', 'Repetition Penalty Range': 'rep_pen_range',
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'Repetition Penalty Slope': 'rep_pen_slope', 'Typical': 'typical', 'Top A': 'top_a',
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'Samplers Order': 'sampler_order', 'Description of settings from the author': 'description',
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'Author': 'Author', 'Model Type': 'Model Type',
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'Description of settings from NovelAI': 'description', 'Model Size': "Model Size"
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}
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df['setting'] = df['setting'].map(settings_mapper)
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try:
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df = df.pivot(index='preset', columns='setting', values='value')
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except:
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print(file)
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display(df)
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raise
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df['Model Type'] = df['Model Type'].str.replace(", ", ",").str.split(",")
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df.loc[:, 'Model Category'] = sheet
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output.append(df)
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#output[sheet] = df.to_json(orient="index")
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df = pd.concat(output)
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df = df.reset_index(drop=False)
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df['uid'] = df.index
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df = df.explode("Model Type")
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df['description'] = df['description'].str.strip()
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with open("official.presets", "w") as f:
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f.write(df.reset_index(drop=True).to_json(orient='records')) |