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MFANN3bv0.7 by netcat420

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  Autotrain compatible   Dataset:netcat420/mfann   Endpoints compatible   Phi   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/netcat420/MFANN3bv0.7 

MFANN3bv0.7 Benchmarks

ARC: 61.69 vs 96.7 (so35)-36.2%
HellaSwag: 75.98 vs 95.3 (gpt4)-20.3%
MMLU: 55.4 vs 88.3 (so35)-37.3%
TruthfulQA: 53.49 vs 59 (gpt4)-9.3%
WinoGrande: 77.66 vs 87.5 (gpt4)-11.2%
GSM8K: 53.68 vs 96.4 (so35)-44.3%
LLME Score: 0.20026
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MFANN3bv0.7 (netcat420/MFANN3bv0.7)

MFANN3bv0.7 Parameters and Internals

Model Type 
text-classification
Additional Notes 
The model excels in Winogrande, indicating strong performance in that specific task.
Training Details 
Data Sources:
MFANN dataset
Methodology:
fine-tuning
Release Notes 
Version:
0.7
Date:
2024-05-05
Notes:
Model version with specific dataset metrics.
LLM NameMFANN3bv0.7
Repository 🤗https://huggingface.co/netcat420/MFANN3bv0.7 
Model Size2.8b
Required VRAM11.1 GB
Updated2025-02-22
Maintainernetcat420
Model Typephi
Model Files  5.0 GB: 1-of-3   5.0 GB: 2-of-3   1.1 GB: 3-of-3
Model ArchitecturePhiForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.40.1
Tokenizer ClassCodeGenTokenizer
Vocabulary Size51200
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than netcat420/MFANN3bv0.7.

Rank the MFANN3bv0.7 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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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227
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