HarithSami/qwen2.5-7b-instruct-arabic-yt-merged
HarithSami/qwen2.5-7b-instruct-arabic-yt-merged is a 7.6 billion parameter instruction-tuned Qwen2.5 model developed by HarithSami. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for general instruction-following tasks, leveraging its Qwen2.5 architecture and 32K context length.
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Model Overview
HarithSami/qwen2.5-7b-instruct-arabic-yt-merged is an instruction-tuned language model with 7.6 billion parameters, built upon the Qwen2.5 architecture. Developed by HarithSami, this model was fine-tuned using the Unsloth library in conjunction with Huggingface's TRL library, which facilitated a 2x faster training process.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit. - Training Efficiency: Leverages Unsloth for optimized and accelerated fine-tuning.
- Context Length: Supports a context window of 32,768 tokens.
- License: Distributed under the Apache-2.0 license.
Use Cases
This model is suitable for a variety of instruction-following tasks, benefiting from its Qwen2.5 foundation and efficient fine-tuning. Its 7.6 billion parameters make it a capable option for applications requiring robust language understanding and generation, particularly where the Qwen2.5 architecture's strengths are advantageous.