metadata
license: cc-by-nc-4.0
language:
- ru
russian-instructions-10k
Russian instruction-following dataset for fine-tuning LLMs. Translated from Alpaca Cleaned with coding/math boost.
| Size | 9,975 examples |
| Language | Russian |
| Format | instruction_ru → output_ru (Alpaca-style) |
| Translation | Gemma 4 26B via llama.cpp API |
| Filtering | All coding + math examples included, remaining sampled from cleaned Alpaca |
| License | Same as Alpaca (CC BY-NC 4.0 / subject to OpenAI ToS) |
Structure
Each entry has two fields:
instruction_ru— Russian instruction (if original had aninput, it's appended as\nInput: ...)output_ru— Russian response
Intended Use
Recommended format is ChatML via apply_chat_template:
messages = [
{"role": "user", "content": instruction_ru},
{"role": "assistant", "content": output_ru},
]
text = tokenizer.apply_chat_template(messages, tokenize=False)
Sample
{
"instruction_ru": "Вам дан список вопросов, классифицируйте каждый из них по одной из следующих пяти категорий: медицина, история, наука, бизнес, искусство.\nInput: Какой стране первой удалось совершить посадку космического аппарата на Луну?",
"output_ru": "Категория этого вопроса: история."
}
Composition
| Category | Count |
|---|---|
| General | ~8,812 |
| Coding | ~560 |
| Math | ~603 |
| Total | 9,975 |