platypus123/Qwen-Z3-Merged

TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:May 26, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

platypus123/Qwen-Z3-Merged is a 7.6 billion parameter Qwen2.5-based instruction-tuned language model developed by platypus123. It was finetuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is optimized for general instruction-following tasks, leveraging its efficient training methodology.

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platypus123/Qwen-Z3-Merged Overview

platypus123/Qwen-Z3-Merged is a 7.6 billion parameter instruction-tuned language model based on the Qwen2.5 architecture. Developed by platypus123, this model was finetuned using the Unsloth library in conjunction with Huggingface's TRL library, which significantly accelerated its training process by a factor of two.

Key Characteristics

  • Base Model: Finetuned from unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit.
  • Efficient Training: Utilizes Unsloth for 2x faster finetuning, making it a resource-efficient option for instruction-following tasks.
  • Parameter Count: Features 7.6 billion parameters, offering a balance between performance and computational requirements.
  • Context Length: Supports a context length of 32768 tokens, suitable for processing longer inputs.

Use Cases

This model is well-suited for general instruction-following applications where efficient training and a robust Qwen2.5 base are beneficial. Its optimized finetuning process makes it a practical choice for developers looking to deploy capable language models without extensive training times.

Finetunes
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