Llama_3.1_8b_Smarteaz_V1.01

Maintained By
Nexesenex

Llama_3.1_8b_Smarteaz_V1.01

PropertyValue
Base ModelLlama 3.1 8B
Model TypeMerged Language Model
Hugging FaceRepository Link
Formatbfloat16

What is Llama_3.1_8b_Smarteaz_V1.01?

Llama_3.1_8b_Smarteaz_V1.01 is a sophisticated merged language model created by Nexesenex, built in the lineage of Smarteaz V1 70B. It represents a successful merge of multiple pre-trained language models using mergekit, specifically designed to serve as a smart building block for more complex 8B parameter implementations.

Implementation Details

The model utilizes the Model Stock merge method, incorporating two key models: Llama_3.1_8b_Smarteaz_0.21_R1 and Llama_3.1_8b_Smarteaz_0.21_SN, both weighted equally at 1.0. The base model is Llama_3.1_8b_Smarteaz_0.11a, and the implementation features normalized weights with a union-based tokenizer approach.

  • Utilizes bfloat16 data type for efficient computation
  • Implements normalized weight distribution
  • Features automatic chat template integration
  • Uses union-source tokenizer configuration

Core Capabilities

  • Outstanding IFEval (0-Shot) performance: 81.51
  • Solid BBH (3-Shot) score: 32.28
  • MATH Level 5 (4-Shot) capability: 23.41
  • Balanced performance across various benchmarks
  • Average performance score: 30.62

Frequently Asked Questions

Q: What makes this model unique?

This model stands out for its balanced approach to merging multiple language models while maintaining high performance on zero-shot inference tasks, particularly evident in its impressive IFEval score of 81.51. It's specifically designed as a building block for more complex implementations, making it valuable for developers looking to build upon its capabilities.

Q: What are the recommended use cases?

Given its performance profile, this model is well-suited for tasks requiring strong reasoning capabilities, particularly in zero-shot and few-shot scenarios. It's especially effective for applications requiring balanced performance across multiple domains, with particular strength in inference tasks.

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