Beast code in Giters

chenshenghao's starred repositories

mt-ranker

Code for the ICLR'24 paper: MT-RANKER : Reference-free machine translation evaluation by inter-system ranking

Language:PythonNOASSERTION900

llama3-from-scratch

llama3 implementation one matrix multiplication at a time

Language:Jupyter NotebookMIT1269600

FeedbackMT

Code of "Improving Machine Translation with Human Feedback: An Exploration of Quality Estimation as a Reward Model"

Language:Python1800

An open-source project dedicated to tracking and segmenting any objects in videos, either automatically or interactively. The primary algorithms utilized include the Segment Anything Model (SAM) for key-frame segmentation and Associating Objects with Transformers (AOT) for efficient tracking and propagation purposes.

Language:Jupyter NotebookAGPL-3.0274400

Zynq7010_eink_controller

这是一个基于Zynq7010的Eink控制器在ED097TC2上高质量显示帧数高达10FPS

Language:CMIT34200

paper2gui

Convert AI papers to GUI，Make it easy and convenient for everyone to use artificial intelligence technology。让每个人都简单方便的使用前沿人工智能技术

Language:Jupyter NotebookMIT1011600

whisper

Robust Speech Recognition via Large-Scale Weak Supervision

Language:PythonMIT6640200

lint-md

:books: 检查中文 markdown 编写格式规范的命令行工具，基于 AST，方便集成 CI，写博客 / 文档必备。支持 API 调用！

Language:TypeScriptMIT92600

document-style-guide

中文技术文档的写作规范

1188900

awesome-i18n

🌍 A curated list of i18n resources for all kind of languages and frameworks

31500

Data-Visualization-with-Python

Discover how Matplotlib and Seaborn can help clearly communicate and present your newly acquired insight

Language:Jupyter NotebookMIT10500

PERT

Pytorch implementation of "A Simple and Strong Baseline: Progressively Region-based Scene Text Removal Networks"

Language:Python400

adaptive-knn-mt

Language:PythonMIT8400

stenella

Code to reproduce results in paper "Levenshtein Training for Word-level Quality Estimation"

Language:PythonMIT300

QE-Reading-List

Machine Translation Quality Estimation Reading List

MIT800

coverage-contrastive-conditioning

Data and code accompanying the paper "As Little as Possible, as Much as Necessary: Detecting Over- and Undertranslations with Contrastive Conditioning" (ACL 2022)

Language:Python2000