PauloIAVPS/ats-qwen2.5-3b

TEXT GENERATIONConcurrency Cost:1Model Size:3.1BQuant:BF16Ctx Length:32kTool Calling:SupportedPublished:Jun 11, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

PauloIAVPS/ats-qwen2.5-3b is a 3.1 billion parameter Qwen2.5-based causal language model developed by PauloIAVPS. This model was finetuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology for practical applications.

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Model Overview

PauloIAVPS/ats-qwen2.5-3b is a 3.1 billion parameter instruction-tuned language model based on the Qwen2.5 architecture. Developed by PauloIAVPS, this model was specifically finetuned from unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit.

Key Characteristics

  • Efficient Training: The model was trained with Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
  • Base Model: Built upon the robust Qwen2.5-3B-Instruct foundation, providing strong general-purpose language understanding and generation capabilities.
  • Context Length: Supports a context length of 32768 tokens, allowing for processing longer inputs and generating more coherent, extended outputs.

Use Cases

This model is suitable for a variety of instruction-following tasks where a balance between performance and computational efficiency is desired. Its optimized training process makes it a practical choice for applications requiring a capable yet lightweight language model.

Finetunes
2 models