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Megatron GPT 2 345M EvolInstruct by KnutJaegersberg

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  Autotrain compatible   Endpoints compatible   Gpt2   Pytorch   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/KnutJaegersberg/megatron-GPT-2-345m-EvolInstruct 

Megatron GPT 2 345M EvolInstruct Benchmarks

ARC: 24.06 vs 96.7 (so35)-75.1%
HellaSwag: 35.12 vs 95.3 (gpt4)-63.1%
MMLU: 24.48 vs 88.3 (so35)-72.3%
TruthfulQA: 41.25 vs 59 (gpt4)-30.1%
WinoGrande: 54.78 vs 87.5 (gpt4)-37.4%
GSM8K: 0.38 vs 96.4 (so35)-99.6%
LLME Score: 0.14471
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Megatron GPT 2 345M EvolInstruct (KnutJaegersberg/megatron-GPT-2-345m-EvolInstruct)
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Megatron GPT 2 345M EvolInstruct Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
Research
Applications:
Benchmarking, Experimental setups
Primary Use Cases:
Text generation tasks
Limitations:
Limited to non-commercial use
Additional Notes 
Benchmark information also includes results on specific open LLM leaderboard metrics.
Supported Languages 
English (fluent)
Training Details 
Data Sources:
Evol-Instruct dataset from WizardLM
Methodology:
Fine-tuning
Model Architecture:
Transformer-based architecture
Input Output 
Input Format:
Text prompts
Accepted Modalities:
text
Output Format:
Generated text
Performance Tips:
Utilize GPUs for optimal performance.
LLM NameMegatron GPT 2 345M EvolInstruct
Repository 🤗https://huggingface.co/KnutJaegersberg/megatron-GPT-2-345m-EvolInstruct 
Model Size345m
Required VRAM1.4 GB
Updated2025-09-07
MaintainerKnutJaegersberg
Model Typegpt2
Model Files  1.4 GB   1.4 GB   0.0 GB
Model ArchitectureGPT2LMHeadModel
Licensecc-by-nc-4.0
Transformers Version4.29.0.dev0
Vocabulary Size50257
Torch Data Typefloat32
Activation Functiongelu_new

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Anwgpt2 345M0K / 1.4 GB320
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Note: green Score (e.g. "73.2") means that the model is better than KnutJaegersberg/megatron-GPT-2-345m-EvolInstruct.

Rank the Megatron GPT 2 345M EvolInstruct Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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