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Mayo by Eric111

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  Merged Model   Autotrain compatible   Conversational   Endpoints compatible   Mistral   Mlabonne/neuralbeagle14-7b   Openchat/openchat-3.5-0106   Region:us   Safetensors   Sharded   Tensorflow

Mayo Benchmarks

ARC: 70.14 vs 96.7 (so35)-27.5%
HellaSwag: 86.27 vs 95.3 (gpt4)-9.5%
MMLU: 65.58 vs 88.3 (so35)-25.7%
TruthfulQA: 60.93 vs 59 (gpt4)3.3%
WinoGrande: 82.16 vs 87.5 (gpt4)-6.1%
GSM8K: 73.39 vs 96.4 (so35)-23.9%
LLME Score: 0.1964
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Mayo Parameters and Internals

LLM NameMayo
Repository 🤗https://huggingface.co/Eric111/Mayo 
Merged ModelYes
Model Size7b
Required VRAM14.4 GB
Updated2024-10-08
MaintainerEric111
Model Typemistral
Model Files  1.9 GB: 1-of-8   1.9 GB: 2-of-8   1.9 GB: 3-of-8   1.9 GB: 4-of-8   2.0 GB: 5-of-8   1.9 GB: 6-of-8   2.0 GB: 7-of-8   0.9 GB: 8-of-8
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16
Mayo (Eric111/Mayo)

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Buddhi 128K Chat 7B128K / 14.4 GB55015
Test001128K / 14.5 GB50
Note: green Score (e.g. "73.2") means that the model is better than Eric111/Mayo.

Rank the Mayo 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 v2024072803
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