The Meta-Llama-3.1-8B-Instruct-Q4_K_M is an 8 billion parameter instruction-tuned generative language model developed by Meta, part of the Llama 3.1 collection. It features an optimized transformer architecture with Grouped-Query Attention and a 128k context length, trained on over 15 trillion tokens with a December 2023 knowledge cutoff. This model is specifically optimized for multilingual dialogue use cases, outperforming many open-source and closed chat models on common industry benchmarks, and supports advanced tool use capabilities.
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trinhvanhung/Meta-Llama-3.1-8B-Instruct-Q4_K_MMost 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.