Understanding the Difficulty of Training Transformers
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Updated
May 31, 2022 - Python
Understanding the Difficulty of Training Transformers
Tensorflow Implementation of "Theory and Experiments on Vector Quantized Autoencoders"
From-scratch Transformer (Vaswani 2017) for zh-en translation. Pure PyTorch, SentencePiece BPE, token-based batching, FP16 training, beam search. Trained on WMT17 (~25M pairs).
The ALLIES Lifelong Learning Machine Translation baseline system's repository
Hunyuan Machine Translation — 🥇 1st in 30/31 WMT25 language pairs
Lara 3 translation outputs on selected WMT25 General MT content
Repo for our attempt at the Shared Task (Quality Estimation) WMT2020. http://www.statmt.org/wmt20/quality-estimation-task.html
Drawer Material Design UI in React Native.
The Suboptimal Quality of WMT Test Sets and Their Impact on HumanParity
React Native Starter Design for application starter design using react native.
Pseudo-reference construction for the WMT26 General MT task: generate-score-select-repair pipeline, per-document provenance, and the analysis behind 'In the Blind' (WMT 2026).
Digests map servers. Point it at an ArcGIS REST, WMS, WFS or WMTS endpoint and get the whole layer out as GeoParquet - natively, on macOS, read-only, resumable.
TamilLingBench: English→Tamil machine translation benchmark for obligatory verb agreement (rationality, gender, number). Tests whether MT evaluation metrics such as COMET, xCOMET, MetricX and CometKiwi catch wrong Tamil agreement. Code, data and model outputs for the WMT 2026 paper "Obligatory Slots".
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