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RuadaptQwen2.5 32B Instruct by msu-rcc-lair

 »  All LLMs  »  msu-rcc-lair  »  RuadaptQwen2.5 32B Instruct   URL Share it on

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  Arxiv:2412.21140   Conversational   Dataset:dichspace/darulm Dataset:ilyagusev/saiga prefer...   Dataset:ilyagusev/saiga scored   Instruct   Lora   Qwen2   Region:us   Ru   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/msu-rcc-lair/RuadaptQwen2.5-32B-instruct 

RuadaptQwen2.5 32B Instruct Benchmarks

LLME Score: 0.25846
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
RuadaptQwen2.5 32B Instruct (msu-rcc-lair/RuadaptQwen2.5-32B-instruct)

RuadaptQwen2.5 32B Instruct Parameters and Internals

Model Type 
text generation
Additional Notes 
The model version is v1 and utilizes a unique tokenization method that significantly improves the generation speed for Russian text.
Supported Languages 
ru (native)
Training Details 
Data Sources:
ru-corpus
Methodology:
Continued pretraining with LEP
Model Architecture:
Qwen2.5 architecture with adapted tokenization
LLM NameRuadaptQwen2.5 32B Instruct
Repository 🤗https://huggingface.co/msu-rcc-lair/RuadaptQwen2.5-32B-instruct 
Model Size32b
Required VRAM65.7 GB
Updated2025-02-07
Maintainermsu-rcc-lair
Model Typeqwen2
Instruction-BasedYes
Model Files  4.8 GB: 1-of-14   4.9 GB: 2-of-14   4.9 GB: 3-of-14   4.9 GB: 4-of-14   4.9 GB: 5-of-14   4.9 GB: 6-of-14   4.9 GB: 7-of-14   4.9 GB: 8-of-14   4.9 GB: 9-of-14   4.9 GB: 10-of-14   4.9 GB: 11-of-14   4.9 GB: 12-of-14   4.9 GB: 13-of-14   2.1 GB: 14-of-14
Supported Languagesru
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.45.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size147200
LoRA ModelYes
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than msu-rcc-lair/RuadaptQwen2.5-32B-instruct.

Rank the RuadaptQwen2.5 32B Instruct Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Release v20241227
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