training and serving facebook nllb 600m model for machine translation from dyula to french
# Translate dyula to French
An example of a machine translation model that translates dyula to French.
## Usage
### Running notebooks
> Make sure you run your notebooks in the relevant virtual environments created below.
1. Set up your environment with the required dependencies.
> You can run these commands from any directory but we recommend running them from the example root directory (where this README is).
- For model serving and inference, set up the `serve` environment by running the following:
> Make sure you uncomment the `ipykernel` requirement in the `requirements.txt` file before running the commands below if you want to run the inference notebook.
```shell
# Use Python 3.10
# Initial setup
python -m venv .serve.venv && source .serve.venv/bin/activate
pip install -r deployment/requirements.txt
# Activate after setup (run every other time)
source .serve.venv/bin/activate
```