From 3920186fc7271efdfacc8b7711f8da9ee06d446b Mon Sep 17 00:00:00 2001 From: AjaySi Date: Thu, 28 Mar 2024 10:53:46 +0530 Subject: [PATCH] main_config changes - WIP --- main_config | 28 ++++++++++++++++++++++++---- 1 file changed, 24 insertions(+), 4 deletions(-) diff --git a/main_config b/main_config index fb696154..242bb635 100644 --- a/main_config +++ b/main_config @@ -56,16 +56,36 @@ num_images = 1 gpt_provider = "openai" # Mention which model of the above provider to use. -model="gpt-3.5-turbo-0125" +model = "gpt-3.5-turbo-0125" # Temperature is a parameter that controls the “creativity” or randomness of the text generated by GPT. # greater determinism and higher values indicating more randomness. # while a lower temperature (e.g., 0.2) makes the output more deterministic and focused (thus, getting flagged as AI content). temperature = 0.6 +# Top-p sampling is particularly useful in scenarios where you want to control the level of diversity in the generated text. +# By adjusting the threshold p, you can influence the diversity of the generated sequences. +# A lower top_p will lead to more diverse but potentially less coherent outputs, +# while a higher top_p will produce more conservative outputs with higher probability tokens. +top_p = 0.9 -top_p=0.9 -max_tokens=4096 -n=1 +# "Max tokens" is a parameter that determines the maximum length of the output sequence generated by a model, +# usually measured in the number of tokens (words or subwords). +# It helps control the length of generated text and manage computational resources during text generation tasks. +max_tokens = 4096 +# "n" represents the number of words or characters grouped together in a sequence when analyzing text. +# For example, if "n" is 2, we're looking at pairs of words (bigrams), +# if "n" is 3, we're looking at groups of three words (trigrams), and so on. +# It helps us understand patterns and relationships between words in a piece of text. +n = 1 +# The frequency penalty parameter, ranging from -1 to 1, influences word selection during text generation. +# Higher values favor less common words, promoting diversity, while lower values favor common words, leading to more predictable text. +frequency_penalty = 1 + +# Presence Penalty encourages the use of diverse words by discouraging repetition. +# It encourages the model to avoid using the same words repeatedly and prompts it to generate varied text by suggesting, +# "Try using different words instead of repeating the same ones." +# from -2 (more flexible while generating text) to 2 (strong discouragement in repetition). +presence_penalty = 1