jburnford/dyslexic-writer-qwen3-4b
TEXT GENERATIONConcurrency Cost:1Model Size:4BQuant:BF16Ctx Length:32kPublished:Feb 17, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Warm
The jburnford/dyslexic-writer-qwen3-4b is a 4 billion parameter Qwen3-based causal language model fine-tuned by jburnford. It specializes in spelling and grammar correction, specifically optimized for assisting dyslexic writers. This model achieves an 85.6% exact match accuracy and an 80.4% error fix rate, making it suitable for dedicated text correction tasks.
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Overview
The jburnford/dyslexic-writer-qwen3-4b is a 4 billion parameter model built upon the Qwen3 architecture, specifically fine-tuned by jburnford for advanced spelling and grammar correction. Its primary focus is to provide robust assistance to dyslexic writers by accurately identifying and correcting textual errors.
Key Capabilities
- Specialized Correction: Optimized for spelling and grammar correction, with a focus on common errors made by dyslexic writers.
- High Accuracy: Achieves an 85.6% Exact Match Accuracy and an 80.4% Error Fix Rate, while preserving correct text with 99.3% No-Error Preservation.
- Extensive Training: Trained on approximately 495,000 examples, including diverse datasets of word pairs, sentence corrections, and paragraph-level error injection from synthetic stories.
- Flexible Deployment: Available for use with both Ollama (GGUF format) and the Hugging Face Transformers library.
Good For
- Automated Proofreading: Ideal for applications requiring automated spelling and grammar checks.
- Dyslexia Support Tools: Excellent for integrating into tools designed to assist dyslexic individuals with writing.
- High-Quality Correction: This 4B parameter variant offers the best quality correction among the
dyslexic-writer-qwen3series, making it suitable for scenarios where accuracy is paramount.