28th November 2023

Release Zephyr 7B GPTQ Model Fine-tuning Framework with 4-Bit Quantization

Zephyr's new framework enhances GPT-Q model performance through fine-tuning and 4-bit quantization, tailored for efficient chatbot interactions.

Availability: The framework is open for exploration and contribution on BayJarvis llm github repo and BayJarvis Blog, offering a new avenue for enhancing chatbot solutions.

Framework Highlights:

• Fine-tuning Workflow: Utilizes zephyr_trainer.py for data preparation and model training, incorporating LoRA modules and quantization for optimized performance.

• Efficiency & Adaptability: Implements gradient checkpointing and precise training arguments, ensuring responsive and effective model behavior.

• Inference Capability: Demonstrated by finetuned_inference.py, the model delivers real-time, context-aware responses, ideal for support scenarios.