BaseLayer/xpand-ai-suppor
The BaseLayer/xpand-ai-suppor is a 7.6 billion parameter Qwen2-based causal language model, developed by BaseLayer. It was fine-tuned using Unsloth and Huggingface's TRL library, enabling 2x faster training. This model is optimized for general instruction-following tasks, leveraging its efficient training methodology to provide robust performance within a 32768 token context window.
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Model Overview
BaseLayer/xpand-ai-suppor is a 7.6 billion parameter instruction-tuned language model, built upon the Qwen2 architecture. Developed by BaseLayer, this model distinguishes itself through its efficient training process, which utilized Unsloth and Huggingface's TRL library. This combination allowed for a reported 2x faster fine-tuning compared to standard methods.
Key Characteristics
- Architecture: Based on the Qwen2 model family.
- Parameter Count: 7.6 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a substantial context window of 32768 tokens, suitable for processing longer inputs and maintaining conversational coherence.
- Training Efficiency: Fine-tuned with Unsloth, which is designed to accelerate the training of large language models.
Use Cases
This model is well-suited for a variety of general-purpose instruction-following applications where efficient performance and a reasonable context window are beneficial. Its optimized training process suggests it could be a good candidate for scenarios requiring rapid deployment or iteration on fine-tuned models.