Example in README.md isn't working

Kernel crashes upon running the code; repeated attempts yield the same error

```
from src.text_clustering import ClusterClassifier
from datasets import load_dataset

SAMPLE = 100_000

texts = load_dataset("HuggingFaceTB/cosmopedia-100k", split="train").select(range(SAMPLE))["text"]

cc = ClusterClassifier(embed_device="mps")

# run the pipeline:
embs, labels, summaries = cc.fit(texts)

# show the results
cc.show()

# save
cc.save("./cc_100k")
```

```
INFO:datasets:PyTorch version 2.2.2 available.
INFO:sentence_transformers.SentenceTransformer:Load pretrained SentenceTransformer: all-MiniLM-L6-v2
The Kernel crashed while executing code in the current cell or a previous cell.
Please review the code in the cell(s) to identify a possible cause of the failure.
Click [here](https://aka.ms/vscodeJupyterKernelCrash) for more info.
View Jupyter [log](command:jupyter.viewOutput) for further details.
```

Start with the README.md example and reproduce it in the Jupyter environment described by the VS Code kernel-crash message. Check the Jupyter output logs and the ClusterClassifier.fit entry point to identify why the 100,000-text pipeline crashes; done means the example completes without crashing and reaches the result display or save step.

Written by the indexing model from the issue text.