sha004ma/en-to-libyan-qwen3b-merged
The sha004ma/en-to-libyan-qwen3b-merged model is a 3.1 billion parameter Qwen2.5-Instruct-based language model developed by sha004ma. It is fine-tuned from unsloth/Qwen2.5-3B-Instruct-bnb-4bit and optimized for performance using Unsloth and Huggingface's TRL library. This model is specifically designed for English to Libyan Arabic translation tasks, leveraging its 32768 token context length for robust language processing.
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Model Overview
The sha004ma/en-to-libyan-qwen3b-merged is a 3.1 billion parameter language model developed by sha004ma. It is fine-tuned from the unsloth/Qwen2.5-3B-Instruct-bnb-4bit base model, leveraging the Qwen2.5-Instruct architecture. This model was trained for enhanced efficiency using the Unsloth library, which facilitates faster training, and Huggingface's TRL library.
Key Capabilities
- Specialized Translation: Primarily designed for English to Libyan Arabic translation.
- Efficient Training: Benefits from Unsloth's optimizations for faster fine-tuning.
- Qwen2.5 Architecture: Built upon the robust Qwen2.5-Instruct foundation.
- Context Length: Supports a substantial context window of 32768 tokens.
Good For
- Developers and researchers focused on English to Libyan Arabic language translation.
- Applications requiring a compact yet capable model for specific regional language tasks.
- Experimenting with models fine-tuned using Unsloth for performance gains.