VLLM
vLLM is a high-performance library tailored for efficient inference and serving of Large Language Models (LLMs). It features advanced PagedAttention for optimal memory ma... vLLM is a high-performance library tailored for efficient inference and serving of Large Language Models (LLMs). It features advanced PagedAttention for optimal memory management, continuous request batching, and CUDA kernel optimizations. With seamless Hugging Face integration, it supports diverse decoding algorithms and various hardware platforms, ensuring rapid and cost-effective model deployment.
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Company Information
- Country: United States
Top VLLM Features
- State-of-the-art serving throughput
- Efficient attention memory management
- PagedAttention mechanism
- Continuous batching of requests
- Fast model execution
- CUDA/HIP graph integration
- Quantization support options
- Optimized CUDA kernels
- FlashAttention integration
- Speculative decoding capabilities
- Chunked prefill functionality
- Seamless HuggingFace integration
- High-throughput decoding algorithms
- Tensor parallelism support
- Pipeline parallelism support
- Streaming output support
- OpenAI-compatible API server
- Multi-lora support
- Compatibility with various hardware
- Community-driven contributions
