Introduction
MS-SWIFT (SWIFT) is a ModelScope community framework for scalable, lightweight fine-tuning, evaluation and deployment of large language models and multimodal models. It supports 500+ text models and 200+ multimodal models, offering CLI, Python API, Gradio UI and server deployment examples.
Key features
- Rich training methods: full-parameter, LoRA, QLoRA, DPO, GRPO, RLHF and more.
- Multimodal and large-model support with extensive examples and datasets.
- Quantization and acceleration backends: vLLM, LMDeploy, GPTQ, AWQ, BNB, etc.
- Multiple interfaces: CLI, Python, Gradio and FastAPI with many ready-to-run scripts.
Use cases
- Large-scale fine-tuning and human-alignment pipelines for research and engineering.
- Multimodal tasks such as VQA, image/audio/video understanding and OCR.
- Quantization, acceleration and distributed training across heterogeneous hardware.
Technical details
- Implemented in Python, compatible with PyTorch and multiple inference engines; documentation is available at the link in frontmatter.
- Licensed under Apache-2.0; active community and regular releases.