trainer.train returns None

Hello there,

In the source code, trainer.train is supposed to return the model path, however, it is returning None for me... is there a way to save the trained model in a specific path? or not saving it at all and use it as a variable?

I have not changed anything in the example code

```
model_path = trainer.train(batch_size=32,
nbits=4, # How many bits will the trained model use when compressing indexes
maxsteps=500000, # Maximum steps hard stop
use_ib_negatives=True, # Use in-batch negative to calculate loss
dim=128, # How many dimensions per embedding. 128 is the default and works well.
learning_rate=5e-6, # Learning rate, small values ([3e-6,3e-5] work best if the base model is BERT-like, 5e-6 is often the sweet spot)
doc_maxlen=256, # Maximum document length. Because of how ColBERT works, smaller chunks (128-256) work very well.
use_relu=False, # Disable ReLU -- doesn't improve performance
warmup_steps="auto", # Defaults to 10%
)

```

Start by tracing the trainer.train entry point used in the example and follow how training output is saved or returned. Reproduce the call shown in the issue, then verify whether the documented behavior is a model path, an in-memory model, or no return value and update the behavior or documentation accordingly.

Written by the indexing model from the issue text.