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Einstein V6.1 LLama3 8B Instruct Ties by Weyaxi

 »  All LLMs  »  Weyaxi  »  Einstein V6.1 LLama3 8B Instruct Ties   URL Share it on

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  Merged Model   Arxiv:2306.01708   Autotrain compatible Base model:meta-llama/meta-lla... Base model:meta-llama/meta-lla... Base model:weyaxi/einstein-v6....   Endpoints compatible   Instruct   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Weyaxi/Einstein-v6.1-LLama3-8B-Instruct-Ties 

Einstein V6.1 LLama3 8B Instruct Ties Benchmarks

ARC: 63.23 vs 96.7 (so35)-34.6%
HellaSwag: 81.56 vs 95.3 (gpt4)-14.4%
MMLU: 68.23 vs 88.3 (so35)-22.7%
TruthfulQA: 52.44 vs 59 (gpt4)-11.1%
WinoGrande: 78.53 vs 87.5 (gpt4)-10.3%
GSM8K: 70.05 vs 96.4 (so35)-27.3%
LLME Score: 0.16437
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Einstein V6.1 LLama3 8B Instruct Ties (Weyaxi/Einstein-v6.1-LLama3-8B-Instruct-Ties)
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Einstein V6.1 LLama3 8B Instruct Ties Parameters and Internals

Additional Notes 
This model is a merge of the models Weyaxi/Einstein-v6.1-Llama3-8B and meta-llama/Meta-Llama-3-8B-Instruct using the TIES merge method.
LLM NameEinstein V6.1 LLama3 8B Instruct Ties
Repository 🤗https://huggingface.co/Weyaxi/Einstein-v6.1-LLama3-8B-Instruct-Ties 
Base Model(s)  Weyaxi/Einstein-v6.1-Llama3-8B   Meta Llama 3 8B Instruct   Meta Llama 3 8B   Weyaxi/Einstein-v6.1-Llama3-8B   meta-llama/Meta-Llama-3-8B-Instruct   meta-llama/Meta-Llama-3-8B
Merged ModelYes
Model Size8b
Required VRAM16.1 GB
Updated2025-09-13
MaintainerWeyaxi
Model Typellama
Instruction-BasedYes
Model Files  10.0 GB: 1-of-2   6.1 GB: 2-of-2
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.39.3
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than Weyaxi/Einstein-v6.1-LLama3-8B-Instruct-Ties.

Rank the Einstein V6.1 LLama3 8B Instruct Ties 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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