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This repository organizes materials, recordings, and schedules related to AI-infra learning meetings.
Based on Nano-vLLM, a simple replication of vLLM with self-contained paged attention and flash attention implementation
MNN: A blazing-fast, lightweight inference engine battle-tested by Alibaba, powering high-performance on-device LLMs and Edge AI.
AISBench Benchmark is a model evaluation tool built on OpenCompass, compatible with OpenCompass’s configuration system, dataset structure, and model backend implementation, while extending support …
An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.
A high-throughput and memory-efficient inference and serving engine for LLMs
Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
The Compute Library is a set of computer vision and machine learning functions optimised for both Arm CPUs and GPUs using SIMD technologies.
Offical PyTorch implementation of "BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework"
JeffreyXiang / nvdiffrec
Forked from NVlabs/nvdiffrecOfficial code for the CVPR 2022 (oral) paper "Extracting Triangular 3D Models, Materials, and Lighting From Images".
Code for 3D object detection for autonomous driving
Native and Compact Structured Latents for 3D Generation
World's first general purpose 3D object detection codebse.
Library for conversion between Traditional and Simplified Chinese
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
pytorch implementation for "PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation" https://arxiv.org/abs/1612.00593
FlashMLA: Efficient Multi-head Latent Attention Kernels
Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".
This is a Chinese translation of the CUDA programming guide
Ongoing research training transformer models at scale
A CPU+GPU Profiling library that provides access to timeline traces and hardware performance counters.
Real-time face swap for PC streaming or video calls