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FastDeploy is an open-source inference and deployment toolkit designed to simplify the process of running and serving deep learning models across a wide range of hardware platforms. Developed within the PaddlePaddle ecosystem, the toolkit focuses on providing high-performance deployment capabilities for modern AI models including large language models and vision-language systems. The platform enables developers to deploy trained models quickly using optimized inference pipelines that support GPUs, specialized AI accelerators, and other hardware architectures. FastDeploy includes advanced acceleration technologies such as speculative decoding, multi-token prediction, and efficient KV cache management to improve throughput and latency during inference. It also offers compatibility with OpenAI-style APIs and vLLM-like interfaces, allowing developers to integrate deployed models easily into existing applications and services.
Features
- High-performance inference toolkit for large language and vision-language models
- Support for multiple hardware platforms including GPUs and AI accelerators
- Advanced inference optimizations such as speculative decoding and KV cache management
- OpenAI-compatible API services for integrating deployed models into applications
- Support for model quantization formats including FP8 and low-bit precision
- Distributed deployment capabilities for scalable production environments
Project Samples
