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SKY Ko Qwen2.5 7B Instruct SFT Step 5000 by SkyOrbis

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SKY Ko Qwen2.5 7B Instruct SFT Step 5000 is an open-source language model by SkyOrbis. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, Instruction-Based, LLM Explorer Score: 0.25.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-7b-ins...   Instruct   Ko   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/SkyOrbis/SKY-Ko-Qwen2.5-7B-Instruct-SFT-step-5000 

SKY Ko Qwen2.5 7B Instruct SFT Step 5000 Benchmarks

MMLU Pro: 35.98
GPQA: 7.05
MUSR: 10.91
BBH: 34.95
IFEval: 38.12 vs 88 (so35)-56.7%
MATH Lvl 5: 21
LLME Score: 0.2479
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
SKY Ko Qwen2.5 7B Instruct SFT Step 5000 (SkyOrbis/SKY-Ko-Qwen2.5-7B-Instruct-SFT-step-5000)
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SKY Ko Qwen2.5 7B Instruct SFT Step 5000 Parameters and Internals

LLM NameSKY Ko Qwen2.5 7B Instruct SFT Step 5000
Repository 🤗https://huggingface.co/SkyOrbis/SKY-Ko-Qwen2.5-7B-Instruct-SFT-step-5000 
Base Model(s)  Qwen/Qwen2.5-7B-Instruct   Qwen/Qwen2.5-7B-Instruct
Model Size7b
Required VRAM15.2 GB
Updated2025-09-17
MaintainerSkyOrbis
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 Languagesko
Model ArchitectureQwen2ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.46.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Qwen2.5 7B Instruct 1M986K / 15.4 GB101838363
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Qwen2.5 7B CelestialHarmony 1M986K / 14.8 GB37
Q2.5 Instruct 1M Harmony986K / 15.2 GB42
Impish QWEN 7B 1M986K / 15.2 GB76
COCO 7B Instruct 1M986K / 15.2 GB184
Apollo 7B986K / 15.2 GB60
Graph R1 7B986K / 15.3 GB53
Qwen2.5 7B Sky R1 Mini986K / 15.2 GB70
Note: green Score (e.g. "73.2") means that the model is better than SkyOrbis/SKY-Ko-Qwen2.5-7B-Instruct-SFT-step-5000.

Rank the SKY Ko Qwen2.5 7B Instruct SFT Step 5000 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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