T-pro 2.0：高效俄罗斯混合推理模型与实验平台

摘要

我们推出T-pro 2.0——一个支持混合推理与高效推理的俄语开源大语言模型。该模型支持直接回答与推理轨迹生成，采用西里尔密集分词器并适配EAGLE推测解码流水线以降低延迟。为促进可复现、可扩展的研究，我们在Hugging Face平台开源了模型权重、T-Wix 50万条指令数据集、T-Math数学推理基准以及EAGLE权重。这些资源使用户能够研究俄语推理机制，并扩展或适配模型及推理流水线。公开的网页演示展示了推理与非推理模式，呈现了我们的推理栈在多领域实现的加速效果。T-pro 2.0由此成为一个易用的开放系统，可用于构建和评估高效实用的俄语大语言模型应用。

English

We introduce T-pro 2.0, an open-weight Russian LLM for hybrid reasoning and efficient inference. The model supports direct answering and reasoning-trace generation, using a Cyrillic-dense tokenizer and an adapted EAGLE speculative-decoding pipeline to reduce latency. To enable reproducible and extensible research, we release the model weights, the T-Wix 500k instruction corpus, the T-Math reasoning benchmark, and the EAGLE weights on Hugging Face. These resources allow users to study Russian-language reasoning and to extend or adapt both the model and the inference pipeline. A public web demo exposes reasoning and non-reasoning modes and illustrates the speedups achieved by our inference stack across domains. T-pro 2.0 thus serves as an accessible open system for building and evaluating efficient, practical Russian LLM applications.

T-pro 2.0：高效俄罗斯混合推理模型与实验平台

T-pro 2.0: An Efficient Russian Hybrid-Reasoning Model and Playground

摘要

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