@PyTorch
Recover more than 70% accuracy degradation from 4-bit quantization using TorchAO’s (https://t.co/Jr0qtnIAgZ) Quantization-Aware Training (QAT), now available through fine-tuning in Unsloth and Axolotl! Following the previous TorchAO QAT blog(https://t.co/kXAGBfOSMZ), the PyTorch team at @Meta extended the TorchAO QAT flow to support an end-to-end GPU server flow, targeting fast CUDA kernels for fast inference in @vllm_project, and integrated this flow into popular fine-tuning frameworks like Unsloth and Axolotl. Read our latest blog: https://t.co/nFx4MYHoRj #PyTorch #vLLM #OpenSourceAI #TorchAO