AduyWp/alpaca-qwen25-finetuned

TEXT GENERATIONConcurrent Unit Cost:1Model Size:3.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Jul 9, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

AduyWp/alpaca-qwen25-finetuned is a 3.1 billion parameter Qwen2.5 instruction-tuned language model developed by AduyWp. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is designed for general language tasks, leveraging its efficient fine-tuning process to provide a capable and accessible LLM.

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Model Overview

AduyWp/alpaca-qwen25-finetuned is a 3.1 billion parameter language model based on the Qwen2.5 architecture, developed by AduyWp. This model has been instruction-tuned to enhance its performance across various language understanding and generation tasks.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Qwen2.5-3B-Instruct-bnb-4bit, indicating a foundation in a robust instruction-following model.
  • Efficient Training: The fine-tuning process utilized Unsloth and Huggingface's TRL library, which allowed for a reported 2x faster training speed. This efficiency can lead to more accessible and iterative model development.
  • Context Length: Supports a substantial context length of 32768 tokens, enabling it to process and generate longer sequences of text.

Use Cases

This model is suitable for a range of applications requiring a capable instruction-tuned language model, particularly where efficient deployment and inference are beneficial due to its 3.1 billion parameter size. Its foundation in the Qwen2.5 series suggests strong general language capabilities.

Finetunes
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