parthbijpuriya/qwen2.5-7b-finetuned-v2

TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kPublished:Apr 10, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The parthbijpuriya/qwen2.5-7b-finetuned-v2 is a 7.6 billion parameter Qwen2.5 model developed by parthbijpuriya, fine-tuned from unsloth/qwen2.5-7b-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general language tasks, leveraging its efficient fine-tuning process to provide a capable language model.

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Model Overview

This model, parthbijpuriya/qwen2.5-7b-finetuned-v2, is a 7.6 billion parameter language model developed by parthbijpuriya. It is a fine-tuned variant of the Qwen2.5 architecture, specifically building upon unsloth/qwen2.5-7b-unsloth-bnb-4bit.

Key Characteristics

  • Efficient Training: The model was fine-tuned with Unsloth and Huggingface's TRL library, which significantly accelerated the training process by a factor of two.
  • Base Model: It leverages the robust capabilities of the Qwen2.5-7B architecture, known for its strong performance across various language understanding and generation tasks.
  • License: The model is released under the Apache-2.0 license, allowing for broad use and distribution.

Use Cases

This fine-tuned Qwen2.5 model is suitable for a range of applications where a capable 7.6 billion parameter language model is beneficial. Its efficient training methodology suggests it could be a good choice for developers looking for a performant model that benefits from optimized fine-tuning techniques.