LMFlow - Fast and Extensible Toolkit for Finetuning and Inference of Large Foundation Models

Some recommends LMFlow, a fast and extensible toolkit for finetuning and inference of large foundation models. It just takes 5 hours on a 3090 GPU for fine-tuning llama-7B.

LMFlow is a powerful toolkit designed to streamline the process of finetuning and performing inference with large foundation models. It provides efficient and scalable solutions for handling large-scale language models. With LMFlow, you can easily experiment with different data sets, training parameters, and architectures to achieve optimal performance.

For more information, you can visit the official LMFlow GitHub repository.

Alpaca LoRA - Efficient Training of Language Models

To train large language models effectively, you can utilize Alpaca LoRA. It is a framework that enables efficient and cost-effective training of language models on GPUs.

With Alpaca LoRA, you can leverage the power of multiple GPUs to accelerate the training process. It optimizes GPU memory consumption and reduces the training time, allowing you to train models like LLaMA 7B in a cost-efficient manner.

For more information and detailed usage instructions, you can visit the Alpaca LoRA GitHub repository.

Tags: LORA, LMFlow, fine-tuning, foundation models, Alpaca LoRA, LLaMA, GitHub repository

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