Cathallama-70B by gbueno86 is a 70 billion parameter instruction-tuned language model with an 8192 token context length, created by merging Meta-Llama-3.1-70B-Instruct, turboderp/Cat-Llama-3-70B-instruct, and Nexusflow/Athene-70B. This model demonstrates a 9% overall success rate increase on MMLU-PRO compared to LLaMA 3.1 70b, showing strong performance across various MMLU-PRO categories. It is designed for general conversational and reasoning tasks, particularly excelling in areas like Psychology, Economics, and Computer Science.
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gbueno86/Cathallama-70BMost commonly used values from Featherless users
temperature
This setting influences the sampling randomness. Lower values make the model more deterministic; higher values introduce randomness. Zero is greedy sampling.
top_p
This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.
top_k
This limits the number of top tokens to consider. Set to -1 to consider all tokens.
frequency_penalty
This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.
presence_penalty
This setting penalizes new tokens based on their presence in the generated text so far. Values > 0 encourage new tokens; < 0 encourages repetition.
repetition_penalty
This setting penalizes new tokens based on their appearance in the prompt and generated text. Values > 1 encourage new tokens; < 1 encourages repetition.
min_p
This setting representing the minimum probability for a token to be considered relative to the most likely token. Must be in [0, 1]. Set to 0 to disable.