surajkyc/qwen3-er-match_notmatch-newapproach-merged2
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Apr 2, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The surajkyc/qwen3-er-match_notmatch-newapproach-merged2 is a 4 billion parameter Qwen3-based instruction-tuned model developed by surajkyc, featuring a 32768 token context length. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is specifically designed for tasks related to entity resolution, focusing on 'match' or 'not match' determinations.
Loading preview...
Model Overview
The surajkyc/qwen3-er-match_notmatch-newapproach-merged2 is a 4 billion parameter language model, fine-tuned by surajkyc. It is based on the Qwen3 architecture and leverages a substantial 32768 token context window, making it suitable for processing extensive inputs.
Key Capabilities
- Entity Resolution (ER): This model is specifically trained for entity resolution tasks, focusing on classifying relationships as 'match' or 'not match'.
- Efficient Fine-tuning: The model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Qwen3 Foundation: Built upon the robust Qwen3 base model, inheriting its general language understanding and generation capabilities.
Good For
- Applications requiring precise 'match' or 'not match' decisions in entity resolution scenarios.
- Developers looking for a Qwen3-based model optimized for specific classification tasks with efficient training origins.