作者称 Oc-e-Non-v1 将 Qwen 平均回答长度缩短 50%
AI 总结
Reddit 用户 /u/-p-e-w- 发布了 Oc-e-Non-v1，这是使用 Heretic 及 config.terse.toml 配置生成的 Qwen3-4B-Instruct-2507 简洁版。作者称，该模型将 Qwen 的平均回答长度缩短 50%，示例显示其输出比关闭推理的 GPT-5.6 Terra 更短。帖子同时指出，Heretic 目前尚不支持控制推理强度。
深度见解
该项目展示了如何用 Heretic 将简洁回答行为嵌入模型，而作者也指出可以通过提示词实现类似效果。其平均回答长度缩短 50% 的说法目前尚未获得独立验证。
Richard I of England was called "Oc-e-Non" (Yes and No in Occitan) by some of contemporaries, supposedly because he used few words.
Wouldn't it be nice if LLMs followed his shining example?
Oc-e-Non-v1 is a tersified version of Qwen3-4B-Instruct-2507. It reduces Qwen's mean response length by 50%. Output examples "What is 1+1?"
GPT-5.6 Terra (reasoning off): 1 + 1 = 2 😊️
Oc-e-Non-v1: 2 "Are dogs mammals?"
GPT-5.6 Terra (reasoning off): Yes. Dogs are mammals: they have hair, are warm-blooded, and mothers nurse their young with milk.
Oc-e-Non-v1: Yes "Write a Python function that checks if a string contains only capital letters."
GPT-5.6 Terra (reasoning off):
You can use Python's built-in isupper() method to check whether a string contains only capital letters. def is_only_uppercase(s): return s.isupper()
Example usage: print(is_only_uppercase("HELLO")) # True print(is_only_uppercase("Hello")) # False print(is_only_uppercase("PYTHON")) # True print(is_only_uppercase("hello123")) # False
Note: isupper() returns True if the string contains at least one uppercase letter and no lowercase letters. Numbers and special characters are allowed.
Oc-e-Non-v1: def contains_only_uppercase(s): return s.isupper() I made this model with Heretic, and you can do the same thing.
Make sure you have the latest master version of Heretic (pip install git+https://github.com/p-e-w/heretic.git), then run Heretic with the config.terse.toml configuration file. That's it!
I used the relatively ancient Qwen3-4B because it is the last native non-thinking version of Qwen I'm aware of, and controlling reasoning effort isn't implemented in Heretic yet.
(Please don't take this too seriously. I know that the same thing can easily be achieved with prompting, but it's interesting that it can also be baked into the model. This is intended as a light-hearted post while we all wait for Qwen4 😉️) submitted by /u/-p-e-w-
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