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Xtuner
Overview :
XTuner is a high-performance, flexible, and feature-rich fine-tuning toolkit designed for large models such as InternLM, Llama, Baichuan, Qwen, and ChatGLM. It supports the pre-training and fine-tuning of LLM and VLM on almost all GPUs, and can automatically schedule high-performance operations like FlashAttention and Triton kernels to enhance training throughput. XTuner is compatible with DeepSpeed and supports various ZeRO optimization techniques. It also supports various LLMs and VLMs, such as LLaVA, and has been designed with robust data pipelines to accommodate any format of datasets. Moreover, XTuner supports multiple training algorithms, including QLoRA, LoRA, and full-parameter fine-tuning, allowing users to choose the solution that best fits their needs.
Target Users :
Designed for developers and data scientists who need to fine-tune and optimize large machine learning models.
Use Cases
Fine-tuning the InternLM2 model on a single GPU using XTuner.
Fine-tuning models larger than 70B parameters in a multi-node environment using XTuner.
Fine-tuning the ChatGLM3 model using XTuner's QLoRA algorithm.
Features
Supports pre-training and fine-tuning of Large Language Models (LLMs) and Vision Language Models (VLMs)
Auto-schedules high-performance operations
Compatible with DeepSpeed and supports ZeRO optimization techniques
Supports various dataset formats
Supports multiple training algorithms
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