Alelcv27/Llama3.1-8B-Base-ModelStock-Math-Code
TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:Apr 25, 2026Architecture:Transformer Cold
Alelcv27/Llama3.1-8B-Base-ModelStock-Math-Code is an 8 billion parameter language model based on Meta's Llama 3.1 architecture, merged using the Model Stock method. This model specifically combines capabilities from Llama3.1-8B-Base-Math and Llama3.1-8B-Base-Code. It is optimized for tasks requiring strong mathematical reasoning and code generation, offering a 32,768 token context window.
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Overview
This model, Alelcv27/Llama3.1-8B-Base-ModelStock-Math-Code, is an 8 billion parameter language model built upon the Meta Llama 3.1-8B base architecture. It was created using the Model Stock merge method, which combines the strengths of multiple pre-trained models.
Key Capabilities
- Enhanced Mathematical Reasoning: Integrates capabilities from a math-focused Llama 3.1-8B base model.
- Improved Code Generation: Incorporates features from a code-focused Llama 3.1-8B base model.
- Llama 3.1 Foundation: Benefits from the robust base performance of Meta's Llama 3.1 series.
- 32K Context Window: Supports a substantial context length of 32,768 tokens, suitable for complex problems.
Good For
- Mathematical Problem Solving: Ideal for applications requiring accurate numerical computations, formula derivation, and logical math reasoning.
- Code Development: Suitable for generating, understanding, and debugging code across various programming languages.
- Technical Applications: Use cases that demand both strong analytical and programming skills from an LLM.