[Feature] Enviformer fine tuning and evaluation

## Changes
- I have finished the backend integration of EnviFormer (#19), this includes, dataset building, model finetuning, model evaluation and model prediction with the finetuned model.
- `PackageBasedModel` has been adjusted to be more abstract, this includes making the `_save_model` method and making `compute_averages` a static class function.
- I had to bump the python-version in `pyproject.toml` to >=3.12 from >=3.11 otherwise uv failed to install EnviFormer.
- The default EnviFormer loading during `settings.py` has been removed.

## Future Fix
I noticed you have a little bit of code in `PackageBasedModel` -> `evaluate_model` for using the `eval_packages` during evaluation instead of train/test splits on `data_packages`. It doesn't seem finished, I presume we want this for all models, so I will take care of that in a new branch/pullrequest after this request is merged.

Also, I haven't done anything for a POST request to finetune the model, I'm not sure if that is something we want now.

Co-authored-by: Liam Brydon <62733830+MyCreativityOutlet@users.noreply.github.com>
Reviewed-on: enviPath/enviPy#141
Reviewed-by: jebus <lorsbach@envipath.com>
Co-authored-by: liambrydon <lbry121@aucklanduni.ac.nz>
Co-committed-by: liambrydon <lbry121@aucklanduni.ac.nz>

envipath/settings.py

@@ -247,13 +247,7 @@ LOGGING = {
 
 # Flags
 ENVIFORMER_PRESENT = os.environ.get('ENVIFORMER_PRESENT', 'False') == 'True'
-if ENVIFORMER_PRESENT:
-    print("Loading enviFormer")
-    device = os.environ.get('ENVIFORMER_DEVICE', 'cpu')
-    from enviformer import load
-    ENVIFORMER_INSTANCE = load(device=device)
-    print("loaded")
-
+ENVIFORMER_DEVICE = os.environ.get('ENVIFORMER_DEVICE', 'cpu')
 
 # If celery is not present set always eager to true which will cause delayed tasks to block until finished
 FLAG_CELERY_PRESENT = os.environ.get('FLAG_CELERY_PRESENT', 'False') == 'True'