Alelcv27/Llama3.2-3B-Base-Math-v2

TEXT GENERATIONConcurrency Cost:1Model Size:3.2BQuant:BF16Ctx Length:32kPublished:Apr 18, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

Alelcv27/Llama3.2-3B-Base-Math-v2 is a 3.2 billion parameter Llama-based language model developed by Alelcv27. This model was fine-tuned using Unsloth and Huggingface's TRL library, resulting in faster training. It is designed for general language tasks, leveraging its Llama architecture for efficient processing.

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Overview

Alelcv27/Llama3.2-3B-Base-Math-v2 is a 3.2 billion parameter language model, developed by Alelcv27. It is based on the Llama architecture, specifically fine-tuned from unsloth/llama-3.2-3b-unsloth-bnb-4bit. The fine-tuning process utilized Unsloth and Huggingface's TRL library, which enabled a 2x faster training time.

Key Characteristics

  • Architecture: Llama-based, fine-tuned from unsloth/llama-3.2-3b-unsloth-bnb-4bit.
  • Parameter Count: 3.2 billion parameters.
  • Training Efficiency: Achieved 2x faster training using Unsloth and Huggingface's TRL library.
  • License: Released under the Apache-2.0 license.

Potential Use Cases

This model is suitable for applications requiring a compact yet capable language model. Its efficient training process suggests it could be a good candidate for scenarios where rapid iteration or deployment on resource-constrained environments is beneficial. While the specific mathematical optimization mentioned in the model name is not detailed in the README, its Llama base provides a strong foundation for various NLP tasks.