FastDeploy provides a multi-tiered acceleration solution:
Hardware-level acceleration::
- Adapted to NVIDIA GPU/XPU/NPU acceleration chips, through themodel.set_backend()Specify the hardware backend
- Use of specialized drivers on devices such as the RK3588 (e.g. rknpu2)
algorithm optimization::
- Enable speculative decoding (model.enable_speculative_decoding()) Improve sequence generation speed
- Multi-token prediction technique to reduce response latency
Model quantification::
- Supports quantization schemes such as W8A16/FP8, typical scenarios can speed up 2-4 times
- Example:model.enable_quantization('W8A16')
Service Layer Optimization::
- Implementing request batch processing in conjunction with vLLM
- Load balancing using OpenAI API-compatible interfaces
This answer comes from the articleFastDeploy: an open source tool for rapid deployment of AI modelsThe
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