amirhosseinjpl/jplstar
amirhosseinjpl/jplstar is a 7.6 billion parameter language model fine-tuned from Qwen/Qwen2.5-7B-Instruct by amirhosseinjpl. This model specializes in dialect transfer, specifically translating Standard Persian into the Abizi dialect. It achieves an 85.8% character overlap metric on its test set for this specific translation task, making it suitable for specialized linguistic applications.
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Model Overview
amirhosseinjpl/jplstar, also known as Telisk 1.0, is a 7.6 billion parameter language model developed by amirhosseinjpl. It is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct specifically designed for dialect transfer. The model's primary function is to translate Standard Persian into the Abizi dialect, with Qaeni also included in the training mix.
Key Capabilities
- Dialect Transfer: Specializes in converting Standard Persian text to the Abizi dialect.
- Fine-tuned Architecture: Built upon the Qwen2.5-7B-Instruct base model.
- Training Method: Utilizes Unsloth QLoRA for efficient fine-tuning, with the adapter merged into the final model.
Performance Metrics
The model was evaluated using a character overlap metric (F1 over character bags after yeh/kaf normalization), as exact match is not suitable due to the unstable nature of Abizi spelling. It achieved:
- Valid Set: 81.5% character overlap (0/30 exact matches)
- Test Set: 85.8% character overlap (0/50 exact matches)
Intended Use
This model is a dialect transfer model and is not intended as a general-purpose chatbot. Its performance is optimized for the specific task of Persian-to-Abizi translation. Users should employ the provided system prompt during inference to ensure the intended dialect transfer behavior, as the base Qwen identity may reappear without it.
Licensing
The fine-tune artifacts are licensed under Apache-2.0, subject to the Qwen2.5-Instruct license of the base model.