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Cybertron V4 Qw7B MGS by fblgit

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  Arxiv:2406.08464   Arxiv:2407.10671   Arxiv:2410.21228   Autotrain compatible Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-7b-ins...   Conversational Dataset:magpie-align/magpie-qw...   En   Endpoints compatible   Generated from trainer   Instruct   Model-index   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/fblgit/cybertron-v4-qw7B-MGS 

Cybertron V4 Qw7B MGS Benchmarks

MMLU Pro: 38.59
GPQA: 8.05
MUSR: 13.2
BBH: 37.04
IFEval: 62.64 vs 88 (so35)-28.8%
MATH Lvl 5: 34.89
LLME Score: 0.30453
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Cybertron V4 Qw7B MGS (fblgit/cybertron-v4-qw7B-MGS)

Cybertron V4 Qw7B MGS Parameters and Internals

LLM NameCybertron V4 Qw7B MGS
Repository 🤗https://huggingface.co/fblgit/cybertron-v4-qw7B-MGS 
Base Model(s)  Qwen/Qwen2.5-7B-Instruct   Qwen/Qwen2.5-7B-Instruct
Model Size7b
Required VRAM15.2 GB
Updated2025-05-31
Maintainerfblgit
Model Typeqwen2
Instruction-BasedYes
Model Files  5.0 GB: 1-of-4   4.9 GB: 2-of-4   5.0 GB: 3-of-4   0.3 GB: 4-of-4
Supported Languagesen
Model ArchitectureQwen2ForCausalLM
Licenseother
Context Length131072
Model Max Length131072
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 fblgit/cybertron-v4-qw7B-MGS.

Rank the Cybertron V4 Qw7B MGS 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  
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Release v20241227
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