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FANNO by ShadowFall09

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  Autotrain compatible   Endpoints compatible   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/ShadowFall09/FANNO 

FANNO Benchmarks

ARC: 55.46 vs 96.7 (so35)-42.6%
HellaSwag: 79.29 vs 95.3 (gpt4)-16.8%
MMLU: 46.58 vs 88.3 (so35)-47.2%
TruthfulQA: 52.05 vs 59 (gpt4)-11.8%
WinoGrande: 74.43 vs 87.5 (gpt4)-14.9%
GSM8K: 14.63 vs 96.4 (so35)-84.8%
LLME Score: 0.20313
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
FANNO (ShadowFall09/FANNO)

FANNO Parameters and Internals

Additional Notes 
FANNO is an innovative, fully autonomous, open-sourced framework designed to streamline the annotation process for instruction datasets without requiring pre-existing annotated data.
LLM NameFANNO
Repository 🤗https://huggingface.co/ShadowFall09/FANNO 
Model Size7b
Required VRAM27.1 GB
Updated2025-02-22
MaintainerShadowFall09
Model Typellama
Model Files  4.8 GB: 1-of-6   4.9 GB: 2-of-6   4.9 GB: 3-of-6   4.9 GB: 4-of-6   4.9 GB: 5-of-6   2.7 GB: 6-of-6
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length2048
Model Max Length2048
Transformers Version4.37.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat32

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Note: green Score (e.g. "73.2") means that the model is better than ShadowFall09/FANNO.

Rank the FANNO 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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Release v20241227
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