Qwen2.5 Coder 7B Instruct NL2SH by westenfelder

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Qwen2.5 Coder 7B Instruct NL2SH is an open-source language model by westenfelder. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, License: mit, Instruction-Based, Code Generating, LLM Explorer Score: 0.17.

  Arxiv:2502.06858 Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-coder-...   Codegen Dataset:westenfelder/nl2sh-alf...   En   Endpoints compatible   Instruct   Model-index   Qwen2   Region:us   Safetensors   Sharded   Tensorflow   Translation

Qwen2.5 Coder 7B Instruct NL2SH Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Qwen2.5 Coder 7B Instruct NL2SH Parameters and Internals

LLM NameQwen2.5 Coder 7B Instruct NL2SH
Repository 🤗https://huggingface.co/westenfelder/Qwen2.5-Coder-7B-Instruct-NL2SH 
Base Model(s)  Qwen/Qwen2.5-Coder-7B-Instruct   Qwen/Qwen2.5-Coder-7B-Instruct
Model Size7b
Required VRAM15.2 GB
Updated2026-05-04
Maintainerwestenfelder
Model Typeqwen2
Instruction-BasedYes
Model Files  4.9 GB: 1-of-4   4.9 GB: 2-of-4   4.3 GB: 3-of-4   1.1 GB: 4-of-4
Supported Languagesen
Generates CodeYes
Model ArchitectureQwen2ForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.46.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|PAD_TOKEN|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than westenfelder/Qwen2.5-Coder-7B-Instruct-NL2SH.

Rank the Qwen2.5 Coder 7B Instruct NL2SH 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 v20260328a