azherali/Riazi-8B-SFT
Riazi-8B-SFT is an 8 billion parameter Qwen3-based causal language model developed by azherali, fine-tuned using Unsloth and Huggingface's TRL library. This model leverages efficient training techniques to enhance performance. It is designed for general language understanding and generation tasks, benefiting from its Qwen3 architecture and optimized training process.
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Model Overview
azherali/Riazi-8B-SFT is an 8 billion parameter language model built upon the Qwen3 architecture. It was developed by azherali and fine-tuned using efficient methods provided by Unsloth and Huggingface's TRL library. This approach allowed for a significantly faster training process, specifically noted as 2x faster.
Key Characteristics
- Base Model: Qwen3-8B, providing a strong foundation for language tasks.
- Efficient Fine-tuning: Utilizes Unsloth for accelerated training, making the development process more efficient.
- Parameter Count: Features 8 billion parameters, balancing capability with computational requirements.
- Context Length: Supports a substantial context window of 32768 tokens, enabling processing of longer inputs and generating more coherent, extended outputs.
Intended Use Cases
This model is suitable for a variety of natural language processing applications where a robust 8B parameter model with an extended context window is beneficial. Its efficient training suggests it could be a good candidate for developers looking for a performant model without the extensive training times typically associated with larger models.