surajkyc/qwen3-er-match_notmatch-merged

TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Mar 30, 2026License:apache-2.0Architecture:Transformer Open Weights Cold

The surajkyc/qwen3-er-match_notmatch-merged is a 4 billion parameter Qwen3 instruction-tuned language model developed by surajkyc. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is designed for specific tasks related to entity resolution, likely involving matching or non-matching scenarios.

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Model Overview

The surajkyc/qwen3-er-match_notmatch-merged is a 4 billion parameter Qwen3-based instruction-tuned language model. Developed by surajkyc, this model leverages the Qwen3 architecture and has been specifically fine-tuned for particular tasks.

Key Characteristics

  • Base Model: Fine-tuned from unsloth/Qwen3-4B-Instruct-2507-unsloth-bnb-4bit.
  • Training Efficiency: The fine-tuning process was significantly accelerated, achieving 2x faster training speeds, by utilizing Unsloth and Huggingface's TRL library.
  • Context Length: Supports a context length of 32768 tokens.

Potential Use Cases

This model is likely optimized for specialized entity resolution (ER) tasks, focusing on scenarios that require determining matches or non-matches between entities. Its instruction-tuned nature suggests it can follow specific prompts for classification or comparison within this domain.