The teknium/Llama-3.1-AlternateTokenizer is an 8 billion parameter instruction-tuned large language model developed by Meta, part of the Llama 3.1 collection. This model utilizes an optimized transformer architecture with Grouped-Query Attention and supports a 128k context length. It is optimized for multilingual dialogue use cases, excelling in assistant-like chat and code generation across supported languages like English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.
Loading preview...
Model tree for
teknium/Llama-3.1-AlternateTokenizerMost 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.