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datasets: |
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- IlyaGusev/saiga_scored |
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- IlyaGusev/saiga_preferences |
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- dichspace/darulm |
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language: |
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- ru |
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pipeline_tag: text-generation |
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base_model: |
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- RefalMachine/ruadapt_qwen2.5_3B_ext_u48_full_lr5e4_peft_mlp_32_32_bs256 |
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--- |
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# Model description |
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Instruction-tuned version of RefalMachine/ruadapt_qwen2.5_3B_ext_u48_full_lr5e4_peft_mlp_32_32_bs256 with extended tokenizer after LEP (Learned Embedding Propagation, paper will be soon) procedure. |
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Thanks to the extended tokenizer, the model works more efficiently with the Russian language (up to 60% speed up compared to Qwen-2.5-3B-Instruct in terms of characters) |
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# How to cite: |
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Tikhomirov M., Chernyshev D. Facilitating large language model Russian adaptation with Learned Embedding Propagation // 2024 (will be soon) |
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Tikhomirov M., Chernyshev D. Impact of Tokenization on LLaMa Russian Adaptation //2023 Ivannikov Ispras Open Conference (ISPRAS). – IEEE, 2023. – С. 163-168. |
