# Convert to Opik format
cc_opik = converter.convert_to_opik_format(
    dataset=cc_dataset,
    input_columns=["text"],
    output_columns=["language"],
    metadata_columns=["url", "timestamp"],
    dataset_name="common-crawl-dataset",
    description="Common Crawl text classification dataset"
)
```

## Results viewing

Once your Hugging Face datasets are converted and uploaded to Opik, you can view them in the Opik UI. Each dataset will contain:

* Input data from specified columns
* Expected output from specified columns
* Metadata from additional columns
* Source information (Hugging Face dataset name and split)

## Feedback Scores and Evaluation

Once your Hugging Face datasets are in Opik, you can evaluate your LLM applications using Opik's evaluation framework:

```python
from opik.evaluation import evaluate
from opik.evaluation.metrics import Hallucination