Repository: Unbabel/COMET
Issue: [QUESTION] Is comet download still a supported command? 
Root cause: Unimplemented Feature Gap

## ❓ Questions and Help

#### What is your question?

Is `comet download` still a supported command? If not, what is the best way to download the data needed to reproduce the results? 

#### Code

```{bash}
$ comet download --help
=>  command not found: comet
$ comet-download --help
=>  command not found: comet-download
```

#### What have you tried?

I tried running `comet download` as specified in `data/README.md`, and I get the error `command not found: comet`. However, `comet-score` and `comet-compare` works, so I know that I did install it. I also tried `comet-download` and still get the same error. 

#### What's your environment?

 - OS: macOS Big Sur 11.5.2
 - Packaging: conda 
 - Version 4.8.3 
 - Python 3.9.7


The download command it's not supported anymore. I'll add a readme with download links for data. 

I have to do that for this year's shared task models also.

Meanwhile, you can use the links from the previous version:

Apequest:
```bash 
wget https://unbabel-experimental-data-sets.s3-eu-west-1.amazonaws.com/comet/hter/apequest.zip
```

QT21:
```bash
wget https://unbabel-experimental-data-sets.s3-eu-west-1.amazonaws.com/comet/hter/qt21.zip
```

WMT 17-> 19:
This includes relative ranks and DA scores.

```bash
wget https://unbabel-experimental-data-sets.s3-eu-west-1.amazonaws.com/comet/da/wmt-metrics.zip
```

@ricardorei This is exactly what I needed. Thank you!

Hi @ricardorei,

Are there already any similar download links for the 2021 shared task? 
Thank you!

Cheers,
Chantal

Hi @chanberg 

This is the link for 2020 DA's:
```bash
wget https://unbabel-experimental-data-sets.s3.eu-west-1.amazonaws.com/wmt/2020-da.csv.tar.gz
```

2020 DA Relative-Ranks:
```bash
wget https://unbabel-experimental-data-sets.s3.eu-west-1.amazonaws.com/wmt/2020-daRR.csv.tar.gz
```

And for the MQM data you have it [here](https://github.com/google/wmt-mqm-human-evaluation) but I'll try to upload the exact files we used after splitting the data and creating the z-scores. I'll try to do that later today or tomorrow..




@ricardorei thank you so much!

@chanberg I also prepared the WMT20 MQM annotated data.

The entire dataset with MQM sentence scores and the corresponding z-score:
```bash
wget https://unbabel-experimental-data-sets.s3.eu-west-1.amazonaws.com/wmt/2020-MQM.csv.tar.gz
```

The train split we used::
```bash
wget https://unbabel-experimental-data-sets.s3.eu-west-1.amazonaws.com/wmt/2020-MQM.train.csv.tar.gz
```

The corresponding test split:
```bash
wget https://unbabel-experimental-data-sets.s3.eu-west-1.amazonaws.com/wmt/2020-MQM.test.csv.tar.gz
```



Don't forget to cite Markus paper if you use this MQM data from 2020: 

```bash
@article{50397,
title	= {Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation},
author	= {Markus Freitag and George Foster and David Grangier and Viresh Ratnakar and Qijun Tan and Wolfgang Macherey},
year	= {2021},
URL	= {https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00437/108866/Experts-Errors-and-Context-A-Large-Scale-Study-of},
journal	= {Transactions of the Association for Computational Linguistics},
pages	= {1460-1474},
volume	= {9}
}
```

and the WMT Metrics/News Translation tasks if you use the direct assessments!



@ricardorei this is great! thank you so much!