RasolKhaled/Ray-3B-IQ_LLM
RasolKhaled/Ray-3B-IQ_LLM is a 3.1 billion parameter Qwen2.5-3B-Instruct model developed by RasolKhaled. This model was finetuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. It is designed for general instruction-following tasks, leveraging its efficient training methodology to provide a capable language model.
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Overview
RasolKhaled/Ray-3B-IQ_LLM is a 3.1 billion parameter language model, specifically a finetuned version of the Qwen2.5-3B-Instruct architecture. Developed by RasolKhaled, this model leverages the Unsloth library in conjunction with Huggingface's TRL library for its training process. This combination allowed for a significant acceleration in training time, reportedly achieving 2x faster finetuning compared to standard methods.
Key Capabilities
- Instruction Following: As an instruction-tuned model, it is designed to understand and execute a wide range of natural language instructions.
- Efficient Training: Benefits from the Unsloth framework, which optimizes the finetuning process for speed and resource efficiency.
- Qwen2.5 Base: Built upon the robust Qwen2.5-3B-Instruct foundation, inheriting its general language understanding and generation capabilities.
Good For
- Developers looking for a compact yet capable instruction-following model.
- Applications requiring efficient deployment of a 3 billion parameter LLM.
- Experimentation with models finetuned using advanced techniques like Unsloth for faster iteration.