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Qwen2.5 Coder Scholar 7B Abliterated MFANN by netcat420

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  Autotrain compatible   Codegen   Conversational   Dataset:netcat420/mfann   En   Endpoints compatible   Instruct   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/netcat420/Qwen2.5-Coder-Scholar-7B-Abliterated-MFANN 

Qwen2.5 Coder Scholar 7B Abliterated MFANN Benchmarks

MMLU Pro: 23.96
GPQA: 5.7
MUSR: 9.63
BBH: 29.98
IFEval: 57.42 vs 88 (so35)-34.8%
MATH Lvl 5: 25.68
LLME Score: 0.31143
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 Scholar 7B Abliterated MFANN (netcat420/Qwen2.5-Coder-Scholar-7B-Abliterated-MFANN)

Qwen2.5 Coder Scholar 7B Abliterated MFANN Parameters and Internals

LLM NameQwen2.5 Coder Scholar 7B Abliterated MFANN
Repository 🤗https://huggingface.co/netcat420/Qwen2.5-Coder-Scholar-7B-Abliterated-MFANN 
Model Size7b
Required VRAM30.5 GB
Updated2025-03-12
Maintainernetcat420
Model Typeqwen2
Instruction-BasedYes
Model Files  5.0 GB: 1-of-7   4.8 GB: 2-of-7   4.9 GB: 3-of-7   4.9 GB: 4-of-7   5.0 GB: 5-of-7   3.7 GB: 6-of-7   2.2 GB: 7-of-7
Generates CodeYes
Model ArchitectureQwen2ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.47.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|im_end|>
Vocabulary Size152064
Torch Data Typefloat32
Errorsreplace

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Note: green Score (e.g. "73.2") means that the model is better than netcat420/Qwen2.5-Coder-Scholar-7B-Abliterated-MFANN.

Rank the Qwen2.5 Coder Scholar 7B Abliterated MFANN 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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