thatsnovaa/ielts-writing-examiner-qwen-merged
TEXT GENERATIONPricing:Input $0.32 / Cached $0.064 / Output $1.6Concurrent Unit Cost:1Model Size:3.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Sep 20, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
The thatsnovaa/ielts-writing-examiner-qwen-merged model is a 3.1 billion parameter Qwen2.5-3B-Instruct causal language model, fine-tuned by thatsnovaa. It was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning. This model is specifically optimized for tasks related to IELTS writing examination, leveraging its Qwen2.5 base for specialized performance in this domain.
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Model Overview
This model, developed by thatsnovaa, is a fine-tuned version of the Qwen2.5-3B-Instruct base model, featuring 3.1 billion parameters and a 32768-token context length. It was specifically trained to serve as an IELTS writing examiner, indicating its specialization in evaluating and providing feedback on IELTS writing tasks.
Key Capabilities
- Specialized for IELTS Writing: The model is fine-tuned for tasks related to the International English Language Testing System (IELTS) writing component.
- Efficient Training: It leverages the Unsloth library and Huggingface's TRL library, which allowed for a 2x faster fine-tuning process.
- Qwen2.5 Architecture: Built upon the Qwen2.5-3B-Instruct foundation, providing a robust base for language understanding and generation.
Good For
- IELTS Preparation: Ideal for users seeking automated evaluation or feedback on their IELTS writing practice.
- Educational Tools: Can be integrated into platforms designed to help students prepare for the IELTS exam.
- Specialized Language Assessment: Useful for applications requiring nuanced understanding and assessment of English writing within a specific academic context.