T-pro-it-2.0-GGUF
π¨ Users are advised to exercise caution and are responsible for any additional training and oversight required to ensure the model's responses meet acceptable ethical and safety standards. The responsibility for incorporating this model into industrial or commercial solutions lies entirely with those who choose to deploy it.
This repository contains T-pro-it-2.0 converted to the GGUF format with
llama.cpp.
See the original BF16 model here: t-tech/T-pro-it-2.0.
π Benchmarks
TBD
Available quantisations
Recommendation: choose the highest-quality quantisation that fits your hardware (VRAM / RAM).
Filename (β -gguf) |
Quant method | Bits | Size (GB) |
|---|---|---|---|
t-pro-it-2.0-q4_k_m |
Q4_K_M | 4 | 19.8 |
t-pro-it-2.0-q5_k_s |
Q5_K_S | 5 | 22.6 |
t-pro-it-2.0-q5_0 |
Q5_0 | 5 | 22.6 |
t-pro-it-2.0-q5_k_m |
Q5_K_M | 5 | 23.2 |
t-pro-it-2.0-q6_k |
Q6_K | 6 | 26.9 |
t-pro-it-2.0-q8_0 |
Q8_0 | 8 | 34.8 |
Size figures assume no GPU off-loading. Off-loading lowers RAM usage and uses VRAM instead.
Quickstart
llama.cpp
Check out our llama.cpp documentation for more usage guide.
We advise you to clone llama.cpp and install it following the official guide. We follow the latest version of llama.cpp.
In the following demonstration, we assume that you are running commands under the repository llama.cpp.
./llama-cli -hf t-tech/T-pro-it-2.0-GGUF:Q8_0 --jinja --color -ngl 99 -fa -sm row --temp 0.6 --presence-penalty 1.0 -c 40960 -n 32768 --no-context-shift
ollama
Check out our ollama documentation for more usage guide.
You can run T-pro-2.0 with one command:
ollama run t-tech/T-pro-it-2.0:q8_0
See also t-tech ollama homepage.
Switching Between Thinking and Non-Thinking Mode
You can add /think and /no_think to user prompts or system messages to switch the model's thinking mode from turn to turn. The model will follow the most recent instruction in multi-turn conversations.
π Citation
If you use this model in your research or projects, please cite:
@inproceedings{stoianov-etal-2026-pro,
title = "{T}-pro 2.0: An Efficient {R}ussian Hybrid-Reasoning Model and Playground",
author = "Stoianov, Dmitrii and
Taranets, Danil and
Tsymboi, Olga and
Latypov, Ramil and
Dautov, Almaz and
Kruglikov, Vladislav and
Nikita, Surkov and
Abramov, German and
Gein, Pavel and
Abulkhanov, Dmitry and
Gashkov, Mikhail and
Zelenkovskiy, Viktor and
Batalov, Artem and
Medvedev, Aleksandr and
Potapov, Anatolii",
editor = "Croce, Danilo and
Leidner, Jochen and
Moosavi, Nafise Sadat",
booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 3: System Demonstrations)",
month = mar,
year = "2026",
address = "Rabat, Marocco",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.eacl-demo.22/",
doi = "10.18653/v1/2026.eacl-demo.22",
pages = "297--319",
ISBN = "979-8-89176-382-1"
}
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