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Alpacino SuperCOT 13B by xzuyn

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  1826   
  Alpaca   Autotrain compatible   Endpoints compatible   Llama   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/xzuyn/Alpacino-SuperCOT-13B 

Alpacino SuperCOT 13B Benchmarks

ARC: 58.36 vs 96.7 (so35)-39.6%
HellaSwag: 81.69 vs 95.3 (gpt4)-14.3%
MMLU: 47.89 vs 88.3 (so35)-45.8%
TruthfulQA: 45.42 vs 59 (gpt4)-23%
WinoGrande: 76.95 vs 87.5 (gpt4)-12.1%
GSM8K: 7.51 vs 96.4 (so35)-92.2%
LLME Score: 0.12617
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Alpacino SuperCOT 13B (xzuyn/Alpacino-SuperCOT-13B)
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Alpacino SuperCOT 13B Parameters and Internals

Additional Notes 
This model was created as an experimental merge of two existing models to test the merging capabilities on a personal computer.
LLM NameAlpacino SuperCOT 13B
Repository 🤗https://huggingface.co/xzuyn/Alpacino-SuperCOT-13B 
Model Size13b
Required VRAM25.9 GB
Updated2025-03-28
Maintainerxzuyn
Model Typellama
Model Files  2.1 GB: 1-of-13   2.0 GB: 2-of-13   2.1 GB: 3-of-13   2.0 GB: 4-of-13   2.0 GB: 5-of-13   2.0 GB: 6-of-13   2.0 GB: 7-of-13   2.1 GB: 8-of-13   2.0 GB: 9-of-13   2.0 GB: 10-of-13   2.0 GB: 11-of-13   2.0 GB: 12-of-13   1.6 GB: 13-of-13
Model ArchitectureLlamaForCausalLM
Context Length2048
Model Max Length2048
Transformers Version4.28.1
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than xzuyn/Alpacino-SuperCOT-13B.

Rank the Alpacino SuperCOT 13B 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 v20241124
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