The Saxo/Linkbricks-Horizon-AI-Korean-Mistral-Nemo-sft-dpo-12B is a 12 billion parameter Korean language model developed by Linkbricks Horizon-AI, fine-tuned from the Mistral-Nemo-Instruct-2407 base model. It was trained using SFT and DPO methods on Korean, Chinese, English, and Japanese cross-training data, including logical data, to enhance its ability to handle complex Korean logic problems. This model is particularly strengthened for high-level analysis of customer reviews, social postings, and coding tasks, featuring a context window size of 128K tokens.
Loading preview...
Quick Stats
423
Model tree for
Saxo/Linkbricks-Horizon-AI-Korean-Mistral-Nemo-sft-dpo-12BMost 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.