Alelcv27/Llama3.1-8B-Code-Math

TEXT GENERATIONConcurrency Cost:1Model Size:8BQuant:FP8Ctx Length:32kPublished:Feb 2, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

Alelcv27/Llama3.1-8B-Code-Math is an 8 billion parameter Llama 3.1 model developed by Alelcv27, specifically fine-tuned for code and mathematical tasks. This model leverages Unsloth and Huggingface's TRL library for accelerated training, offering enhanced performance in programming and numerical reasoning. With a 32768 token context length, it is designed for developers requiring robust capabilities in technical problem-solving and code generation.

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Overview

Alelcv27/Llama3.1-8B-Code-Math is an 8 billion parameter language model, developed by Alelcv27, that has been fine-tuned from the base Alelcv27/Llama3.1-8B-Code model. This iteration focuses on enhancing its capabilities in both code and mathematical domains, making it a specialized tool for technical applications.

Key Characteristics

  • Base Model: Fine-tuned from Alelcv27/Llama3.1-8B-Code, which is based on the Llama 3.1 architecture.
  • Parameter Count: Features 8 billion parameters, balancing performance with computational efficiency.
  • Training Optimization: The model was trained using Unsloth and Huggingface's TRL library, resulting in a 2x faster training process.
  • Context Length: Supports a substantial context window of 32768 tokens, beneficial for complex coding problems and multi-step mathematical reasoning.

Ideal Use Cases

  • Code Generation and Completion: Excels in generating and completing programming code across various languages.
  • Mathematical Problem Solving: Suited for tasks requiring numerical reasoning, equation solving, and mathematical proofs.
  • Technical Development: Useful for developers and researchers working on projects that demand strong code and math capabilities from an LLM.

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