-
Nokia Bell Labs
- Paris
- https://ztz1989.github.io/
- https://orcid.org/0000-0002-2781-7120
Starred repositories
Python client for Batfish: https://github.com/batfish/batfish
Introduction to Machine Learning Systems
Pretrain, finetune and serve LLMs on Intel platforms with Ray
Experiments for distributed optimization algorithms
Pytorch implementation of preconditioned stochastic gradient descent (Kron and affine preconditioner, low-rank approximation preconditioner and more)
Packet-level simulation code to model Opera and other networks from the 2020 NSDI paper "Expanding across time to deliver bandwidth efficieny and low latency"
This repository contains the artifact for the Middleware'24 paper: "PvCC: A vCPU Scheduling Policy for DPDK-applied Systems at Multi-Tenant Edge Data Centers"
[ICLR 2022] The implementation for the paper "Equivariant Graph Mechanics Networks with Constraints".
Customize, control, and enhance LLM generation with logits processors, featuring visualization capabilities to inspect and understand state transitions
The LLM's practical guide: From the fundamentals to deploying advanced LLM and RAG apps to AWS using LLMOps best practices
Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
Free hands-on course about Graph Neural Networks using PyTorch Geometric.
Shooting Large-scale Traffic Engineering by Combining Deep Learning and Optimization Approach (CoNEXT'25)
An extremely fast Python package and project manager, written in Rust.
Wasm powered Jupyter running in the browser 💡
A collection of tools, code, and documentation to understand the host network on real server hardware.
Network Automation and Programmability Abstraction Layer with Multivendor support
Sketchable function and density simulations for data science
This is the code repository of our submission: Understanding the Dark Side of LLMs’ Intrinsic Self-Correction.
Reference implementation for the TupleMerge packet classifier
Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray
Benchmark for evaluating LLMs in network configuration problems.
Distributed AI with the Ray Framework Course