Add a PyTorch NLP fine tuning notebook using the IMDb dataset for sentiment analysis (#453)

* Add the pytorch IMDB fine tuning notebook

* Update markdown

* Add README

* Renaming notebook and main doc update

* Fix link

* fix path in readme

* Update requirements.txt

* Add datasets to requirements

* Add transformers to requirements

* add sklearn to requirements

* Updates based on review feedback - fixing 'extends pytorch

* Update the README to specify 3.9

Author: dmsuehir

docs/notebooks/transfer_learning/README.md

@@ -10,7 +10,8 @@ and [Intel Extension for PyTorch](https://github.com/intel/intel-extension-for-p
 | ---------| ----------|-------------|
 | [BERT Classifier fine tuning using the Model Zoo for Intel Architecture](/docs/notebooks/transfer_learning/bert_classifier_fine_tuning/) | TensorFlow | Fine tunes BERT base from the Model Zoo for Intel Architecture using the IMDB movie review dataset, then quantizes the saved model using the [Intel® Neural Compressor](https://github.com/intel/neural-compressor) |
 | [BERT SQuAD fine tuning with TF Hub](/docs/notebooks/transfer_learning/tfhub_bert/) | TensorFlow | Demonstrates BERT fine tuning using scripts from the [TensorFlow Model Garden](https://github.com/tensorflow/models) and the [SQuAD dataset](https://rajpurkar.github.io/SQuAD-explorer/). The notebook allows for selecting a BERT large or BERT base model from [TF Hub](https://tfhub.dev). The fine tuned model is evaluated and exported as a saved model. |
-| [BERT Binary Text Classification with TF Hub](/docs/notebooks/transfer_learning/tfhub_bert) | TensorFlow |Demonstrates BERT binary text classification fine tuning using the [IMDb movie review dataset](https://www.tensorflow.org/datasets/catalog/imdb_reviews) from [TensorFlow Datasets](https://www.tensorflow.org/datasets) or a custom dataset. The notebook allows for selecting a BERT encoder (BERT large, BERT base, or small BERT) to use along with a preprocessor from [TF Hub](https://tfhub.dev). The fine tuned model is evaluated and exported as a saved model. |
+| [BERT Binary Text Classification with TF Hub](/docs/notebooks/transfer_learning/tfhub_bert) | TensorFlow | Demonstrates BERT binary text classification fine tuning using the [IMDb movie review dataset](https://www.tensorflow.org/datasets/catalog/imdb_reviews) from [TensorFlow Datasets](https://www.tensorflow.org/datasets) or a custom dataset. The notebook allows for selecting a BERT encoder (BERT large, BERT base, or small BERT) to use along with a preprocessor from [TF Hub](https://tfhub.dev). The fine tuned model is evaluated and exported as a saved model. |
+| [Text Classifier fine tuning with PyTorch & Hugging Face](/docs/notebooks/transfer_learning/pytorch_text_classification) | PyTorch | Demonstrates fine tuning [Hugging Face models](https://huggingface.co/models) to do sentiment analysis using the IMDb movie review dataset with [Intel® Extension for PyTorch*](https://github.com/intel/intel-extension-for-pytorch) |
 
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