gangyeolkim/llama-3-chat
TEXT GENERATIONConcurrency Cost:1Published On:Jul 5, 2025License:apache-2.0Open Weights Warm

The gangyeolkim/llama-3-chat is an 8 billion parameter instruction-tuned language model, based on allganize/Llama-3-Alpha-Ko-8B-Instruct, designed for chat applications. It features a context length of 8192 tokens and is specifically configured for conversational AI in Korean. This model excels at generating coherent and contextually relevant responses while adhering to defined conversational rules, such as avoiding profanity.

Loading preview...

Parameters:8BContext length:8kArchitecture:TransformerPrecision:FP8Quantized variants:Available
0.0M0.0K

Model tree for

gangyeolkim/llama-3-chat
Popular Sampler Settings

Most 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.