Saxo/Linkbricks-Horizon-AI-Japanese-Superb-V4-70B

Saxo/Linkbricks-Horizon-AI-Japanese-Superb-V4-70B is a 70 billion parameter Japanese-enhanced language model developed by Saxo (Yunsung Ji) of Linkbricks Horizon-AI. Fine-tuned using SFT and DPO on 30 million Japanese news and wiki corpora, it excels in cross-lingual tasks (Japanese, Korean, Chinese, English) and complex logical reasoning. The model is particularly strong in high-dimensional analysis of customer reviews, social posts, coding, writing, mathematics, and logical decision-making, featuring a 128k context window and Function Calling support.

Warm
Public
70B
FP8
32768
License: apache-2.0
Hugging Face

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.