Slovenian LLM eval

Currently supported:

• ARC-Challenge

What we want to support:

• Common sense reasoning: Hellaswag, Winogrande, PIQA, OpenbookQA, ARC-Easy, ARC-Challenge
• World knowledge: NaturalQuestions, TriviaQA
• Reading comprehension: BoolQ

Please email me at gordicaleksa at gmail com in case you're willing to sponsor the automated GPT-4 effort. You will get the credits and eternal glory. :)

Creating the eval - instructions

IMPORTANT

• running this this will eat your google cloud credits or will bill you if you're already in the billing mode (this happens after you spend free credits and then deliberately enable billing again).

• you can use your free credits to translate 500.000 chars / month!

• if this is the first time you're creating a gcloud project you'll have 300$ of free credits!

• sync with Aleksa in Discord in slovenian-eval channel on which tasks to tackle next.

Prerequisites

Before you begin, ensure you meet the following requirements:

For Linux Users:

• Git and Miniconda

For Windows Users: 1. Windows Subsystem for Linux (WSL2). If you don't have WSL2 installed, follow these steps in Windows cmd/powershell in administrator mode:

```bash
wsl --install

// Check version and distribution name. wsl -l -v

// Set the newly downloaded linux distro as default.
wsl --set-default <distribution name>
```

1. Install Git from the WSL terminal.

   bash sudo apt update sudo apt install git git --version

2. Install Miniconda from the WSL terminal. ```bash mkdir -p ~/miniconda3

   wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh

   bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3

   rm -rf ~/miniconda3/miniconda.sh

   // Initialize conda with bash. ~/miniconda3/bin/conda init bash ```

3. Follow the instructions below on WSL.

Instructions for translating lm harness eval from English into Slovenian

First let's setup a minimal Python program that makes sure you can run Google Translate on your local machine.

1. Create a Google Console project (https://console.cloud.google.com/)
2. Enable Google Translation API -> to enable it you have to setup the billing and input your credit card details (a note regarding safety: you'll have 300$ of free credit (if this is the first time you're doing it) and no one can spend money from your credit card unless all those free credits are spent and you re-enable the billing again! if you already had it setup in that case you have 500.000 chars/month for free!)

3. Install Google Cloud CLI (gsutil) on your machine (see this: https://cloud.google.com/storage/docs/gsutil_install/)

   a.) Download the Linux archive file (find latest version from link above)

   curl -O https://dl.google.com/dl/cloudsdk/channels/rapid/downloads/google-cloud-cli-455.0.0-linux-x86_64.tar.gz

   b.) Extract the contents from the archive file above.

   tar -xf google-cloud-cli-455.0.0-linux-x86_64.tar.gz

   c.) Run installation script. ./google-cloud-sdk/install.sh

   d.) Initiate and authenticate your account. ./google-cloud-sdk/bin/gcloud init

   e.) Create a credentials file with gcloud auth application-default login

4. Create and setting up the conda env

   a.) Open a terminal (if on Windows use the WSL terminal, if you're on Linux just use your terminal conda will already be in the PATH)

   b.) Run conda create -n open_nllb python=3.10 -y

   c.) Run conda activate open_nllb

   d.) Run pip install google-cloud-translate

That's it! After that just create a test.py Python file with the following code and run with Run and Debug option in VS code after creating the launch.json file:

```Python from google.cloud import translate

client = translate.TranslationServiceClient() location = "global" projectid="" parent = f"projects/{projectid}/locations/{location}"

response = client.translatetext( request={ "parent": parent, "contents": ["How do you do? Translate this."], "mimetype": "text/plain", "sourcelanguagecode": "en-US", "targetlanguagecode": "sl", } ) valuetranslated = response.translations[0].translatedtext print(value_translated) ```

Running translation of evals from English into Slovenian

Follow these instructions (see below for more details): 1. Create a Python env for this project 2. You'll find the program arguments are already specified inside .vscode/launch.json 3. Change translation_project_id to the google project id you got in the previous section 4. Specify amount of characters you're willing to translate (500_000 is the usual free monthly limit) 5. Run the main.py

Create Python environment

You can reuse the above conda env open-nllb. Next up navigate to the root of the project and run pip install -e .

If you encounter any issue please report immediately on Discord! :) We'll fix it quickly.

Run translation

Finally run (note model and model_args are not important for us but we need to specify them):

python main.py \ --model hf \ --model_args pretrained=mistralai/Mistral-7B-v0.1 \ --tasks <task> \ --translation_project_id <your project id> --char_limit 500000 --start_from_doc_index 0

or open main.py and run using vscode debugger.

Note: * again please sync on Discord about which tasks you should help to translate! :) * select only one task at a time, posssible options: hellaswag,winogrande,piqa,openbookqa,arc_easy,arc_challenge,nq_open,triviaqa,boolq * start_from_doc_index is used if you want to resume and translate a particular task only starting from a certain document index (useful in a collaborative setting where multiple people are translating different portions of the task)

Credits

todo after the project is completed