feature/Add support for hf datasets for text classification task

[Prikshit7766]

Checklist:

• I've added Google style docstrings to my code.
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• The Harness class for Hugging Face and text classification supports the data parameter, which can also be specified as a dictionary with the following attributes: name, subset, feature_column, target_column, and split.
• By default, the split is set to "test," while the default names for the feature and target columns are "text" and "label" respectively.
• This implementation provides users with the flexibility to load their desired dataset according to their specific requirements.

Please find below the code snippet showcasing the utilization of the Harness class for the support of HF Datasets:

harness = Harness(task="text-classification", hub="huggingface", model="nlptown/flaubert_small_cased_sentiment",
                    data={
                        "name": "amazon_reviews_multi",
                        "subset": "en",
                        "feature_column": "review_body",
                        "target_column": "product_category",
                        "split": "train"
                    })