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Urd Qwen2.5 7B by win10

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Urd Qwen2.5 7B is an open-source language model by win10. Features: 7b LLM, VRAM: 16.2GB, Context: 32K, Instruction-Based, Code Generating, Merged, LLM Explorer Score: 0.17.

  Merged Model   Arxiv:2306.01708 Base model:maywell/qwen2-7b-mu... Base model:qwen/qwen2.5-coder-...   Codegen   Conversational   Endpoints compatible   Instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/win10/Urd-Qwen2.5-7B 

Urd Qwen2.5 7B Benchmarks

LLME Score: 0.16542
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Urd Qwen2.5 7B (win10/Urd-Qwen2.5-7B)
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Urd Qwen2.5 7B Parameters and Internals

LLM NameUrd Qwen2.5 7B
Repository 🤗https://huggingface.co/win10/Urd-Qwen2.5-7B 
Base Model(s)  Qwen2 7B Multilingual RP   Qwen/Qwen2.5-Coder-7B-Instruct   maywell/Qwen2-7B-Multilingual-RP   Qwen/Qwen2.5-Coder-7B-Instruct
Merged ModelYes
Model Size7b
Required VRAM16.2 GB
Updated2026-03-29
Maintainerwin10
Model Typeqwen2
Instruction-BasedYes
Model Files  1.1 GB: 1-of-30   1.1 GB: 2-of-30   0.5 GB: 3-of-30   0.5 GB: 4-of-30   0.5 GB: 5-of-30   0.5 GB: 6-of-30   0.5 GB: 7-of-30   0.5 GB: 8-of-30   0.5 GB: 9-of-30   0.5 GB: 10-of-30   0.5 GB: 11-of-30   0.5 GB: 12-of-30   0.5 GB: 13-of-30   0.5 GB: 14-of-30   0.5 GB: 15-of-30   0.5 GB: 16-of-30   0.5 GB: 17-of-30   0.5 GB: 18-of-30   0.5 GB: 19-of-30   0.5 GB: 20-of-30   0.5 GB: 21-of-30   0.5 GB: 22-of-30   0.5 GB: 23-of-30   0.5 GB: 24-of-30   0.5 GB: 25-of-30   0.5 GB: 26-of-30   0.5 GB: 27-of-30   0.5 GB: 28-of-30   0.5 GB: 29-of-30   0.5 GB: 30-of-30
Generates CodeYes
Model ArchitectureQwen2ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.45.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than win10/Urd-Qwen2.5-7B.

Rank the Urd Qwen2.5 7B 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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