🤗 Transformers Notebooks

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.

Hugging Face’s notebooks 🤗

Notebook Description
Getting Started Tokenizers How to train and use your very own tokenizer Open In Colab
Getting Started Transformers How to easily start using transformers Open In Colab
How to use Pipelines Simple and efficient way to use State-of-the-Art models on downstream tasks through transformers Open In Colab
How to train a language model Highlight all the steps to effectively train Transformer model on custom data Open in Colab
How to generate text How to use different decoding methods for language generation with transformers Open in Colab
How to export model to ONNX Highlight how to export and run inference workloads through ONNX
How to use Benchmarks How to benchmark models with transformers Open in Colab

Community notebooks:

Notebook Description Author
Train T5 on TPU How to train T5 on SQUAD with Transformers and Nlp Suraj Patil Open In Colab
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 Open In Colab
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 Open In Colab
Long Sequence Modeling with Reformer How to train on sequences as long as 500,000 tokens with Reformer Patrick von Platen Open In Colab
Fine-tune BART for Summarization How to fine-tune BART for summarization with fastai using blurr Wayde Gilliam Open In Colab
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 Open In Colab
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 Open In Colab
Pretrain Longformer How to build a "long" version of existing pretrained models Iz Beltagy Open In Colab
Fine-tune Longformer for QA How to fine-tune longformer model for QA task Suraj Patil Open In Colab
Evaluate Model with 🤗nlp How to evaluate longformer on TriviaQA with nlp Patrick von Platen Open In Colab
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 Open In Colab
Fine-tune DistilBert for Multiclass Classification How to fine-tune DistilBert for multiclass classification with PyTorch Abhishek Kumar Mishra Open In Colab
Fine-tune BERT for Multi-label Classification How to fine-tune BERT for multi-label classification using PyTorch Abhishek Kumar Mishra Open In Colab
Fine-tune T5 for Summarization How to fine-tune T5 for summarization in PyTorch and track experiments with WandB Abhishek Kumar Mishra Open In Colab
Speed up Fine-Tuning in Transformers with Dynamic Padding / Bucketing How to speed up fine-tuning by a factor of 2 using dynamic padding / bucketing Michael Benesty Open In Colab
Pretrain Reformer for Masked Language Modeling How to train a Reformer model with bi-directional self-attention layers Patrick von Platen Open In Colab