Omkar2118/datasets huggingface dataset:
Amharic - English Parallel Corpus for Machine Translation

**Amharic - English Parallel Corpus for Machine Translation** contains 33,955 sentence pairs extracted text from such news platforms as Ethiopian Press Agency1, Fana Broadcasting Corporate2, and Walta Information Center3. As the data we used is from different sources, it includes various domains such as religious (Bible and Quran), politics, economics, sports, news, among others.

Source: [The Effect of Normalization for Bi-directional Amharic-English Neural Machine Translation](https://arxiv.org/pdf/2210.15224v1.pdf)

Introducing paper: The Effect of Normalization for Bi-directional Amharic-English Neural Machine Translation
DIALOCONAN

**DIALOCONAN** is a dataset comprising over 3000 fictitious multi-turn dialogues between a hater and an NGO operator, covering 6 targets of hate.

Source: [Human-Machine Collaboration Approaches to Build a Dialogue Dataset for Hate Speech Countering](https://arxiv.org/pdf/2211.03433v1.pdf)

Image Source: [https://arxiv.org/pdf/2211.03433v1.pdf](https://arxiv.org/pdf/2211.03433v1.pdf)

Introducing paper: Human-Machine Collaboration Approaches to Build a Dialogue Dataset for Hate Speech Countering
CoP3D

**CoP3D** is a collection of crowd-sourced videos showing around 4,200 distinct pets. CoP2D is a large-scale datasets for benchmarking non-rigid 3D reconstruction "in the wild".

Introducing paper: Common Pets in 3D: Dynamic New-View Synthesis of Real-Life Deformable Categories