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VLSP2025 LegalSML Qwen3 1.7B Legal Pretrain by nqdhocai

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VLSP2025 LegalSML Qwen3 1.7B Legal Pretrain is an open-source language model by nqdhocai. Features: 1.7b LLM, VRAM: 6.9GB, Context: 32K, LLM Explorer Score: 0.19.

  Arxiv:1910.09700   Conversational   Endpoints compatible   Qwen3   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/nqdhocai/VLSP2025-LegalSML-qwen3-1.7b-legal-pretrain 

VLSP2025 LegalSML Qwen3 1.7B Legal Pretrain Benchmarks

LLME Score: 0.19366
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
VLSP2025 LegalSML Qwen3 1.7B Legal Pretrain (nqdhocai/VLSP2025-LegalSML-qwen3-1.7b-legal-pretrain)
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VLSP2025 LegalSML Qwen3 1.7B Legal Pretrain Parameters and Internals

LLM NameVLSP2025 LegalSML Qwen3 1.7B Legal Pretrain
Repository 🤗https://huggingface.co/nqdhocai/VLSP2025-LegalSML-qwen3-1.7b-legal-pretrain 
Model Size1.7b
Required VRAM6.9 GB
Updated2026-05-07
Maintainernqdhocai
Model Typeqwen3
Model Files  5.0 GB: 1-of-2   1.9 GB: 2-of-2
Model ArchitectureQwen3ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.51.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typefloat32
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than nqdhocai/VLSP2025-LegalSML-qwen3-1.7b-legal-pretrain.

Rank the VLSP2025 LegalSML Qwen3 1.7B Legal Pretrain 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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