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MFANN3bv0.9 by netcat420

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  Autotrain compatible   Dataset:netcat420/mfann   En   Endpoints compatible   Phi   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/netcat420/MFANN3bv0.9 

MFANN3bv0.9 Benchmarks

ARC: 61.18 vs 96.7 (so35)-36.7%
HellaSwag: 76.03 vs 95.3 (gpt4)-20.2%
MMLU: 55.18 vs 88.3 (so35)-37.5%
TruthfulQA: 54.24 vs 59 (gpt4)-8.1%
WinoGrande: 77.51 vs 87.5 (gpt4)-11.4%
GSM8K: 54.44 vs 96.4 (so35)-43.5%
LLME Score: 0.20204
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MFANN3bv0.9 (netcat420/MFANN3bv0.9)

MFANN3bv0.9 Parameters and Internals

Model Type 
text-classification
Additional Notes 
The dataset is ever-expanding.
Supported Languages 
en (unknown)
Training Details 
Data Sources:
netcat420/MFANN
Methodology:
fine-tuning
Release Notes 
Version:
0.9
Date:
2024-05-14
Notes:
Fine-tuned on the MFANN dataset.
LLM NameMFANN3bv0.9
Repository 🤗https://huggingface.co/netcat420/MFANN3bv0.9 
Model Size2.8b
Required VRAM11.1 GB
Updated2025-02-17
Maintainernetcat420
Model Typephi
Model Files  5.0 GB: 1-of-3   5.0 GB: 2-of-3   1.1 GB: 3-of-3
Supported Languagesen
Model ArchitecturePhiForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.40.2
Tokenizer ClassCodeGenTokenizer
Vocabulary Size51200
Torch Data Typefloat16

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MFANN3bv0.24128K / 11.1 GB160
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Note: green Score (e.g. "73.2") means that the model is better than netcat420/MFANN3bv0.9.

Rank the MFANN3bv0.9 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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