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Top Down Introduction to BERT with HuggingFace and PyTorch
I will also provide some intuition into how BERT works with a top down approach (applications to algorithm).
bert top-down huggingface pytorch
PyTorch Transformers Tutorials
A set of annotated Jupyter notebooks, that give user a template to fine-tune transformers model to downstream NLP tasks such as classification, NER etc.
transformers text-classification text-summarization named-entity-recognition
Paraphrase Any Question with T5 (Text-To-Text Transformer)
Given a question, generate paraphrased versions of the question with T5 transformer. Pretrained model and training script provided.
t5 transformers huggingface pytorch
Summary of 🤗 Transformers Models
A high-level summary of the differences between each model in HuggingFace's Transformer library.
transformers huggingface summary natural-language-processing
Generate Boolean (Yes/No) Questions From Any Content
Question generation algorithm trained on the BoolQ dataset using T5 text-to-text transformer model.
question-generation transformers huggingface t5
Simple Transformers: Transformers Made Easy
Simple Transformers removes complexity and lets you get down to what matters – model training and experimenting with the Transformer model architectures.
transformers huggingface simple-transformers text-classification
Transformers - Hugging Face
🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.
transformers huggingface attention bert
Topic Modeling with BERT
Leveraging 🤗 Transformers and a class-based TF-IDF to create dense clusters allowing for easily interpretable topics.
bert topic-modeling transformers code
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