anyscale / llm-continuous-batching-benchmarks
☆117Updated last year
Alternatives and similar repositories for llm-continuous-batching-benchmarks:
Users that are interested in llm-continuous-batching-benchmarks are comparing it to the libraries listed below
- ☆185Updated 6 months ago
- Official repository for LightSeq: Sequence Level Parallelism for Distributed Training of Long Context Transformers☆207Updated 7 months ago
- ☆103Updated 7 months ago
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆303Updated 9 months ago
- PyTorch bindings for CUTLASS grouped GEMM.☆118Updated 3 months ago
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆247Updated 5 months ago
- A low-latency & high-throughput serving engine for LLMs☆337Updated 2 months ago
- Dynamic Memory Management for Serving LLMs without PagedAttention☆345Updated 2 weeks ago
- Applied AI experiments and examples for PyTorch☆256Updated 3 weeks ago
- 🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.☆192Updated this week
- Boosting 4-bit inference kernels with 2:4 Sparsity☆72Updated 7 months ago
- Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity☆204Updated last year
- Zero Bubble Pipeline Parallelism☆381Updated this week
- Easy and Efficient Quantization for Transformers☆195Updated 2 months ago
- ☆78Updated 2 weeks ago
- ☆91Updated 7 months ago
- Latency and Memory Analysis of Transformer Models for Training and Inference☆403Updated last month
- [ICLR2025] Breaking Throughput-Latency Trade-off for Long Sequences with Speculative Decoding☆112Updated 4 months ago
- Fast low-bit matmul kernels in Triton☆285Updated this week
- Simple implementation of Speculative Sampling in NumPy for GPT-2.☆93Updated last year
- Transformer related optimization, including BERT, GPT☆59Updated last year
- LLM Serving Performance Evaluation Harness☆75Updated last month
- ☆139Updated 11 months ago
- ☆127Updated 3 months ago
- Code repo for the paper "LLM-QAT Data-Free Quantization Aware Training for Large Language Models"☆279Updated last month
- ☆241Updated this week
- ☆66Updated 2 weeks ago
- A collection of memory efficient attention operators implemented in the Triton language.☆262Updated 10 months ago
- Summary of system papers/frameworks/codes/tools on training or serving large model☆56Updated last year
- An easy-to-use package for implementing SmoothQuant for LLMs☆96Updated last week