You can find here a list of the official notebooks provided by Hugging Face.
Also, we would like to list here interesting content created by the community. If you wrote some notebook(s) leveraging transformers and would like be listed here, please open a Pull Request so it can be included under the Community notebooks.
| Notebook | Description | |
|---|---|---|
| Getting Started Tokenizers | How to train and use your very own tokenizer |  |
| Getting Started Transformers | How to easily start using transformers | |
| How to use Pipelines | Simple and efficient way to use State-of-the-Art models on downstream tasks through transformers | |
| How to train a language model | Highlight all the steps to effectively train Transformer model on custom data | |
| How to generate text | How to use different decoding methods for language generation with transformers | |
| How to export model to ONNX | Highlight how to export and run inference workloads through ONNX |
| Notebook | Description | Author | |
|---|---|---|---|
| Train T5 on TPU | How to train T5 on SQUAD with Transformers and Nlp | Suraj Patil | |
| Fine-tune T5 for Classification and Multiple Choice | How to fine-tune T5 for classification and multiple choice tasks using a text-to-text format with PyTorch Lightning | Suraj Patil | |
| Fine-tune DialoGPT on New Datasets and Languages | How to fine-tune the DialoGPT model on a new dataset for open-dialog conversational chatbots | Nathan Cooper | |
| Long Sequence Modeling with Reformer | How to train on sequences as long as 500,000 tokens with Reformer | Patrick von Platen | |
| Fine-tune BART for Summarization | How to fine-tune BART for summarization with fastai using blurr | Wayde Gilliam | |
| Fine-tune a pre-trained Transformer on anyone's tweets | How to generate tweets in the style of your favorite Twitter account by fine-tune a GPT-2 model | Boris Dayma | |
| A Step by Step Guide to Tracking Hugging Face Model Performance | A quick tutorial for training NLP models with HuggingFace and & visualizing their performance with Weights & Biases | Jack Morris | |
| Pretrain Longformer | How to build a "long" version of existing pretrained models | Iz Beltagy | |
| Fine-tune Longformer for QA | How to fine-tune longformer model for QA task | Suraj Patil | |
| Evaluate Model with 🤗nlp | How to evaluate longformer on TriviaQA with nlp |
Patrick von Platen | |
| Fine-tune T5 for Sentiment Span Extraction | How to fine-tune T5 for sentiment span extraction using a text-to-text format with PyTorch Lightning | Lorenzo Ampil | |
| Fine-tune DistilBert for Multiclass Classification | How to fine-tune DistilBert for multiclass classification with PyTorch | Abhishek Kumar Mishra | |
| Fine-tune BERT for Multi-label Classification | How to fine-tune BERT for multi-label classification using PyTorch | Abhishek Kumar Mishra | |
| Fine-tune T5 for Summarization | How to fine-tune T5 for summarization in PyTorch and track experiments with WandB | Abhishek Kumar Mishra | |