Train a 70b language model on a 2X RTX 3090/4090 with QLoRA and FSDP

Answers.ai has introduced a method to train large language models, such as Llama 2 70B, on limited GPU resources by utilizing fsdp_qlora, an open-source software that leverages QLoRA and FSDP. QLoRA combines quantization with Low-Rank Adaptation to train models larger than available GPU memory, albeit with some limitations related to GPU costs and memory constraints. FSDP, developed by Meta, enables efficient model training by sharding parameters across multiple GPUs, surpassing the prior DDP approach that required fitting the full model on each GPU. The guide outlines steps to rent a 2X RTX 4090 instance on Vast.ai, set up an account, and implement fsdp_qlora for model training, along with optional tools like HQQ for quantization. Troubleshooting advice is offered for instances where GPUs are not recognized, with support available via Vast.ai's chat feature.

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