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65 lines
9.1 KiB
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65 lines
9.1 KiB
Markdown
<!---
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Copyright 2020 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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-->
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# 🤗 Transformers Notebooks
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You can find here a list of the official notebooks provided by Hugging Face.
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Also, we would like to list here interesting content created by the community.
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If you wrote some notebook(s) leveraging 🤗 Transformers and would like be listed here, please open a
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Pull Request so it can be included under the Community notebooks.
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## Hugging Face's notebooks 🤗
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### Documentation notebooks
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You can open any page of the documentation as a notebook in colab (there is a button directly on said pages) but they are also listed here if you need to:
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| Notebook | Description | |
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|:----------|:-------------|------:|
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| [Quicktour of the library](https://github.com/huggingface/notebooks/blob/master/transformers_doc/quicktour.ipynb) | A presentation of the various APIs in Transformers | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/transformers_doc/quicktour.ipynb) |
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| [Summary of the tasks](https://github.com/huggingface/notebooks/blob/master/transformers_doc/task_summary.ipynb) | How to run the models of the Transformers library task by task | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/transformers_doc/task_summary.ipynb) |
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| [Preprocessing data](https://github.com/huggingface/notebooks/blob/master/transformers_doc/preprocessing.ipynb) | How to use a tokenizer to preprocess your data | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/transformers_doc/preprocessing.ipynb) |
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| [Fine-tuning a pretrained model](https://github.com/huggingface/notebooks/blob/master/transformers_doc/training.ipynb) | How to use the Trainer to fine-tune a pretrained model | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/transformers_doc/training.ipynb) |
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| [Summary of the tokenizers](https://github.com/huggingface/notebooks/blob/master/transformers_doc/tokenizer_summary.ipynb) | The differences between the tokenizers algorithm | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/transformers_doc/tokenizer_summary.ipynb) |
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| [Multilingual models](https://github.com/huggingface/notebooks/blob/master/transformers_doc/multilingual.ipynb) | How to use the multilingual models of the library | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/transformers_doc/multilingual.ipynb) |
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| [Fine-tuning with custom datasets](https://github.com/huggingface/notebooks/blob/master/transformers_doc/custom_datasets.ipynb) | How to fine-tune a pretrained model on various tasks | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/transformers_doc/custom_datasets.ipynb) |
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### Examples
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| Notebook | Description | |
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|:----------|:-------------|------:|
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| [Train your tokenizer](https://github.com/huggingface/notebooks/blob/master/examples/tokenizer_training.ipynb) | How to train and use your very own tokenizer |[](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/tokenizer_training.ipynb) |
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| [Train your language model](https://github.com/huggingface/notebooks/blob/master/examples/language_modeling_from_scratch.ipynb) | How to easily start using transformers | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/language_modeling_from_scratch.ipynb) |
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| [How to fine-tune a model on text classification](https://github.com/huggingface/notebooks/blob/master/examples/text_classification.ipynb) | Show how to preprocess the data and fine-tune a pretrained model on any GLUE task. | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/text_classification.ipynb)|
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| [How to fine-tune a model on language modeling](https://github.com/huggingface/notebooks/blob/master/examples/language_modeling.ipynb) | Show how to preprocess the data and fine-tune a pretrained model on a causal or masked LM task. | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/language_modeling.ipynb)|
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| [How to fine-tune a model on token classification](https://github.com/huggingface/notebooks/blob/master/examples/token_classification.ipynb) | Show how to preprocess the data and fine-tune a pretrained model on a token classification task (NER, PoS). | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/token_classification.ipynb)|
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| [How to fine-tune a model on question answering](https://github.com/huggingface/notebooks/blob/master/examples/question_answering.ipynb) | Show how to preprocess the data and fine-tune a pretrained model on SQUAD. | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/question_answering.ipynb)|
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| [How to fine-tune a model on multiple choice](https://github.com/huggingface/notebooks/blob/master/examples/multiple_choice.ipynb) | Show how to preprocess the data and fine-tune a pretrained model on SWAG. | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/multiple_choice.ipynb)|
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| [How to fine-tune a model on translation](https://github.com/huggingface/notebooks/blob/master/examples/translation.ipynb) | Show how to preprocess the data and fine-tune a pretrained model on WMT. | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/translation.ipynb)|
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| [How to fine-tune a model on summarization](https://github.com/huggingface/notebooks/blob/master/examples/summarization.ipynb) | Show how to preprocess the data and fine-tune a pretrained model on XSUM. | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/summarization.ipynb)|
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| [How to train a language model from scratch](https://github.com/huggingface/blog/blob/master/notebooks/01_how_to_train.ipynb)| Highlight all the steps to effectively train Transformer model on custom data | [](https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/01_how_to_train.ipynb)|
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| [How to generate text](https://github.com/huggingface/blog/blob/master/notebooks/02_how_to_generate.ipynb)| How to use different decoding methods for language generation with transformers | [](https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/02_how_to_generate.ipynb)|
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| [How to export model to ONNX](https://github.com/huggingface/notebooks/blob/master/examples/onnx-export.ipynb) | Highlight how to export and run inference workloads through ONNX |
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| [How to use Benchmarks](https://github.com/huggingface/transformers/notebooks/blob/master/examples/benchmark.ipynb) | How to benchmark models with transformers | [](https://colab.research.google.com/github/huggingface/notebooks/blob/master/examples/benchmark.ipynb)|
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| [Reformer](https://github.com/huggingface/blog/blob/master/notebooks/03_reformer.ipynb) | How Reformer pushes the limits of language modeling | [](https://colab.research.google.com/github/patrickvonplaten/blog/blob/master/notebooks/03_reformer.ipynb)|
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## Community notebooks:
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More notebooks developed by the community are available [here](https://huggingface.co/transformers/master/community.html#community-notebooks).
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