* Using loaded checkpoint with --do_predict
Without this fix, I'm getting near-random validation performance for a trained model, and the validation performance differs per validation run. I think this happens since the `model` variable isn't set with the loaded checkpoint, so I'm using a randomly initialized model. Looking at the model activations, they differ each time I run evaluation (but they don't with this fix).
* Update checkpoint loading
* Fixing model loading
* ✨ Alter base pl transformer to use automodels
* 🐛 Add batch size env variable to function call
* 💄 Apply black code style from Makefile
* 🚚 Move lightning base out of ner directory
* ✨ Add lightning glue example
* 💄 self
* move _feature_file to base class
* ✨ Move eval logging to custom callback
* 💄 Apply black code style
* 🐛 Add parent to pythonpath, remove copy command
* 🐛 Add missing max_length kwarg
