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/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingpytorch-nlp | .md | | [How to fine-tune a model on translation](https://github.com/huggingface/notebooks/blob/main/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/main/examples/translation.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/translation.ipynb)| | 30_3_16 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingpytorch-nlp | .md | | [How to fine-tune a model on summarization](https://github.com/huggingface/notebooks/blob/main/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/main/examples/summarization.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/summarization.ipynb)| | 30_3_18 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingpytorch-nlp | .md | | [How to train a language model from scratch](https://github.com/huggingface/blog/blob/main/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/main/notebooks/01_how_to_train.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/blog/blob/main/notebooks/01_how_to_train.ipynb)| | 30_3_20 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingpytorch-nlp | .md | | [How to generate text](https://github.com/huggingface/blog/blob/main/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/main/notebooks/02_how_to_generate.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/blog/blob/main/notebooks/02_how_to_generate.ipynb)| | 30_3_22 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingpytorch-nlp | .md | | [How to generate text (with constraints)](https://github.com/huggingface/blog/blob/main/notebooks/53_constrained_beam_search.ipynb)| How to guide language generation with user-provided constraints | [](https://colab.research.google.com/github/huggingface/blog/blob/main/notebooks/53_constrained_beam_search.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/blog/blob/main/notebooks/53_constrained_beam_search.ipynb)| | 30_3_24 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingpytorch-nlp | .md | | [Reformer](https://github.com/huggingface/blog/blob/main/notebooks/03_reformer.ipynb)| How Reformer pushes the limits of language modeling | [](https://colab.research.google.com/github/patrickvonplaten/blog/blob/main/notebooks/03_reformer.ipynb)| [](https://studiolab.sagemaker.aws/import/github/patrickvonplaten/blog/blob/main/notebooks/03_reformer.ipynb)| | 30_3_25 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#computer-visionpytorch-cv | .md | | Notebook | Description | | | | 30_4_0 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#computer-visionpytorch-cv | .md | |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------:| | 30_4_1 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#computer-visionpytorch-cv | .md | | [How to fine-tune a model on image classification (Torchvision)](https://github.com/huggingface/notebooks/blob/main/examples/image_classification.ipynb) | Show how to preprocess the data using Torchvision and fine-tune any pretrained Vision model on Image Classification | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb)| | 30_4_3 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#computer-visionpytorch-cv | .md | | [How to fine-tune a model on image classification (Albumentations)](https://github.com/huggingface/notebooks/blob/main/examples/image_classification_albumentations.ipynb) | Show how to preprocess the data using Albumentations and fine-tune any pretrained Vision model on Image Classification | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification_albumentations.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/image_classification_albumentations.ipynb)| | 30_4_5 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#computer-visionpytorch-cv | .md | | [How to fine-tune a model on image classification (Kornia)](https://github.com/huggingface/notebooks/blob/main/examples/image_classification_kornia.ipynb) | Show how to preprocess the data using Kornia and fine-tune any pretrained Vision model on Image Classification | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification_kornia.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/image_classification_kornia.ipynb)| | 30_4_7 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#computer-visionpytorch-cv | .md | | [How to perform zero-shot object detection with OWL-ViT](https://github.com/huggingface/notebooks/blob/main/examples/zeroshot_object_detection_with_owlvit.ipynb) | Show how to perform zero-shot object detection on images with text queries | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/zeroshot_object_detection_with_owlvit.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/zeroshot_object_detection_with_owlvit.ipynb)| | 30_4_9 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#computer-visionpytorch-cv | .md | | [How to fine-tune an image captioning model](https://github.com/huggingface/notebooks/blob/main/examples/image_captioning_blip.ipynb) | Show how to fine-tune BLIP for image captioning on a custom dataset | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_captioning_blip.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/image_captioning_blip.ipynb)| | 30_4_11 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#computer-visionpytorch-cv | .md | | [How to build an image similarity system with Transformers](https://github.com/huggingface/notebooks/blob/main/examples/image_similarity.ipynb) | Show how to build an image similarity system | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_similarity.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/image_similarity.ipynb)| | 30_4_13 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#computer-visionpytorch-cv | .md | | [How to fine-tune a SegFormer model on semantic segmentation](https://github.com/huggingface/notebooks/blob/main/examples/semantic_segmentation.ipynb) | Show how to preprocess the data and fine-tune a pretrained SegFormer model on Semantic Segmentation | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/semantic_segmentation.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/semantic_segmentation.ipynb)| | 30_4_15 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#computer-visionpytorch-cv | .md | | [How to fine-tune a VideoMAE model on video classification](https://github.com/huggingface/notebooks/blob/main/examples/video_classification.ipynb) | Show how to preprocess the data and fine-tune a pretrained VideoMAE model on Video Classification | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/video_classification.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/video_classification.ipynb)| | 30_4_17 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#audiopytorch-audio | .md | | Notebook | Description | | |
|:----------|:-------------|:-------------|------:| | 30_5_0 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#audiopytorch-audio | .md | | [How to fine-tune a speech recognition model in English](https://github.com/huggingface/notebooks/blob/main/examples/speech_recognition.ipynb)| Show how to preprocess the data and fine-tune a pretrained Speech model on TIMIT | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/speech_recognition.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/speech_recognition.ipynb)| | 30_5_2 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#audiopytorch-audio | .md | | [How to fine-tune a speech recognition model in any language](https://github.com/huggingface/notebooks/blob/main/examples/multi_lingual_speech_recognition.ipynb)| Show how to preprocess the data and fine-tune a multi-lingually pretrained speech model on Common Voice | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/multi_lingual_speech_recognition.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/multi_lingual_speech_recognition.ipynb)| | 30_5_4 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#audiopytorch-audio | .md | | [How to fine-tune a model on audio classification](https://github.com/huggingface/notebooks/blob/main/examples/audio_classification.ipynb)| Show how to preprocess the data and fine-tune a pretrained Speech model on Keyword Spotting | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/audio_classification.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/audio_classification.ipynb)| | 30_5_6 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#biological-sequencespytorch-bio | .md | | Notebook | Description | | |
|:----------|:----------------------------------------------------------------------------------------|:-------------|------:| | 30_6_0 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#biological-sequencespytorch-bio | .md | | [How to fine-tune a pre-trained protein model](https://github.com/huggingface/notebooks/blob/main/examples/protein_language_modeling.ipynb) | See how to tokenize proteins and fine-tune a large pre-trained protein "language" model | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/protein_language_modeling.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/protein_language_modeling.ipynb) | | 30_6_2 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#biological-sequencespytorch-bio | .md | | [How to generate protein folds](https://github.com/huggingface/notebooks/blob/main/examples/protein_folding.ipynb) | See how to go from protein sequence to a full protein model and PDB file | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/protein_folding.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/protein_folding.ipynb) | | 30_6_4 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#biological-sequencespytorch-bio | .md | | [How to fine-tune a Nucleotide Transformer model](https://github.com/huggingface/notebooks/blob/main/examples/nucleotide_transformer_dna_sequence_modelling.ipynb) | See how to tokenize DNA and fine-tune a large pre-trained DNA "language" model | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/nucleotide_transformer_dna_sequence_modelling.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/nucleotide_transformer_dna_sequence_modelling.ipynb) | | 30_6_6 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#biological-sequencespytorch-bio | .md | | [Fine-tune a Nucleotide Transformer model with LoRA](https://github.com/huggingface/notebooks/blob/main/examples/nucleotide_transformer_dna_sequence_modelling_with_peft.ipynb) | Train even larger DNA models in a memory-efficient way | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/nucleotide_transformer_dna_sequence_modelling_with_peft.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/nucleotide_transformer_dna_sequence_modelling_with_peft.ipynb) | | 30_6_8 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#other-modalitiespytorch-other | .md | | Notebook | Description | | |
|:----------|:----------------------------------------------------------------------------------------|:-------------|------:| | 30_7_0 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#other-modalitiespytorch-other | .md | | [Probabilistic Time Series Forecasting](https://github.com/huggingface/notebooks/blob/main/examples/time-series-transformers.ipynb) | See how to train Time Series Transformer on a custom dataset | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/time-series-transformers.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/time-series-transformers.ipynb) | | 30_7_2 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#utility-notebookspytorch-utility | .md | | Notebook | Description | | |
|:----------|:-------------|:-------------|------:| | 30_8_0 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#utility-notebookspytorch-utility | .md | | [How to export model to ONNX](https://github.com/huggingface/notebooks/blob/main/examples/onnx-export.ipynb)| Highlight how to export and run inference workloads through ONNX | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/onnx-export.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/onnx-export.ipynb)| | 30_8_2 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#utility-notebookspytorch-utility | .md | | [How to use Benchmarks](https://github.com/huggingface/notebooks/blob/main/examples/benchmark.ipynb)| How to benchmark models with transformers | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/benchmark.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/benchmark.ipynb)| | 30_8_3 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingtensorflow-nlp | .md | | Notebook | Description | | |
|:----------|:-------------|:-------------|------:| | 30_9_0 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingtensorflow-nlp | .md | | [Train your tokenizer](https://github.com/huggingface/notebooks/blob/main/examples/tokenizer_training.ipynb) | How to train and use your very own tokenizer |[](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/tokenizer_training.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/tokenizer_training.ipynb)| | 30_9_2 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingtensorflow-nlp | .md | | [Train your language model](https://github.com/huggingface/notebooks/blob/main/examples/language_modeling_from_scratch-tf.ipynb) | How to easily start using transformers |[](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/language_modeling_from_scratch-tf.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/language_modeling_from_scratch-tf.ipynb)| | 30_9_4 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingtensorflow-nlp | .md | | [How to fine-tune a model on text classification](https://github.com/huggingface/notebooks/blob/main/examples/text_classification-tf.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/main/examples/text_classification-tf.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification-tf.ipynb)| | 30_9_6 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingtensorflow-nlp | .md | | [How to fine-tune a model on language modeling](https://github.com/huggingface/notebooks/blob/main/examples/language_modeling-tf.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/main/examples/language_modeling-tf.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/language_modeling-tf.ipynb)| | 30_9_8 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingtensorflow-nlp | .md | | [How to fine-tune a model on token classification](https://github.com/huggingface/notebooks/blob/main/examples/token_classification-tf.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/main/examples/token_classification-tf.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/token_classification-tf.ipynb)| | 30_9_10 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingtensorflow-nlp | .md | | [How to fine-tune a model on question answering](https://github.com/huggingface/notebooks/blob/main/examples/question_answering-tf.ipynb)| Show how to preprocess the data and fine-tune a pretrained model on SQUAD. | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/question_answering-tf.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/question_answering-tf.ipynb)| | 30_9_12 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingtensorflow-nlp | .md | | [How to fine-tune a model on multiple choice](https://github.com/huggingface/notebooks/blob/main/examples/multiple_choice-tf.ipynb)| Show how to preprocess the data and fine-tune a pretrained model on SWAG. | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/multiple_choice-tf.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/multiple_choice-tf.ipynb)| | 30_9_14 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingtensorflow-nlp | .md | | [How to fine-tune a model on translation](https://github.com/huggingface/notebooks/blob/main/examples/translation-tf.ipynb)| Show how to preprocess the data and fine-tune a pretrained model on WMT. | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/translation-tf.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/translation-tf.ipynb)| | 30_9_16 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#natural-language-processingtensorflow-nlp | .md | | [How to fine-tune a model on summarization](https://github.com/huggingface/notebooks/blob/main/examples/summarization-tf.ipynb)| Show how to preprocess the data and fine-tune a pretrained model on XSUM. | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/summarization-tf.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/summarization-tf.ipynb)| | 30_9_18 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#computer-visiontensorflow-cv | .md | | Notebook | Description | | | | 30_10_0 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#computer-visiontensorflow-cv | .md | |:---------------------------------------------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------|:-------------|------:| | 30_10_1 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#computer-visiontensorflow-cv | .md | | [How to fine-tune a model on image classification](https://github.com/huggingface/notebooks/blob/main/examples/image_classification-tf.ipynb) | Show how to preprocess the data and fine-tune any pretrained Vision model on Image Classification | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification-tf.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/image_classification-tf.ipynb)| | 30_10_3 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#computer-visiontensorflow-cv | .md | | [How to fine-tune a SegFormer model on semantic segmentation](https://github.com/huggingface/notebooks/blob/main/examples/semantic_segmentation-tf.ipynb) | Show how to preprocess the data and fine-tune a pretrained SegFormer model on Semantic Segmentation | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/semantic_segmentation-tf.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/semantic_segmentation-tf.ipynb)| | 30_10_5 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#biological-sequencestensorflow-bio | .md | | Notebook | Description | | |
|:----------|:-------------|:-------------|------:| | 30_11_0 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#biological-sequencestensorflow-bio | .md | | [How to fine-tune a pre-trained protein model](https://github.com/huggingface/notebooks/blob/main/examples/protein_language_modeling-tf.ipynb) | See how to tokenize proteins and fine-tune a large pre-trained protein "language" model | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/protein_language_modeling-tf.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/protein_language_modeling-tf.ipynb) | | 30_11_2 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#utility-notebookstensorflow-utility | .md | | Notebook | Description | | |
|:----------|:-------------|:-------------|------:| | 30_12_0 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#utility-notebookstensorflow-utility | .md | | [How to train TF/Keras models on TPU](https://github.com/huggingface/notebooks/blob/main/examples/tpu_training-tf.ipynb) | See how to train at high speed on Google's TPU hardware | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/tpu_training-tf.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/tpu_training-tf.ipynb) | | 30_12_2 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#optimum-notebooks | .md | 🤗 [Optimum](https://github.com/huggingface/optimum) is an extension of 🤗 Transformers, providing a set of performance optimization tools enabling maximum efficiency to train and run models on targeted hardwares.
| Notebook | Description | | |
|:----------|:-------------|:-------------|------:| | 30_13_0 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#optimum-notebooks | .md | | [How to quantize a model with ONNX Runtime for text classification](https://github.com/huggingface/notebooks/blob/main/examples/text_classification_quantization_ort.ipynb)| Show how to apply static and dynamic quantization on a model using [ONNX Runtime](https://github.com/microsoft/onnxruntime) for any GLUE task. | [ for any GLUE task. | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_ort.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_ort.ipynb)| | 30_13_3 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#optimum-notebooks | .md | | [How to quantize a model with Intel Neural Compressor for text classification](https://github.com/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb)| Show how to apply static, dynamic and aware training quantization on a model using [Intel Neural Compressor (INC)](https://github.com/intel/neural-compressor) for any GLUE task. | [ for any GLUE task. | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb)| | 30_13_6 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#optimum-notebooks | .md | | [How to fine-tune a model on text classification with ONNX Runtime](https://github.com/huggingface/notebooks/blob/main/examples/text_classification_ort.ipynb)| Show how to preprocess the data and fine-tune a model on any GLUE task using [ONNX Runtime](https://github.com/microsoft/onnxruntime). | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification_ort.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification_ort.ipynb)| | 30_13_8 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#optimum-notebooks | .md | | [How to fine-tune a model on summarization with ONNX Runtime](https://github.com/huggingface/notebooks/blob/main/examples/summarization_ort.ipynb)| Show how to preprocess the data and fine-tune a model on XSUM using [ONNX Runtime](https://github.com/microsoft/onnxruntime). | [](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/summarization_ort.ipynb)| [](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/summarization_ort.ipynb)| | 30_13_10 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/notebooks.md | https://huggingface.co/docs/transformers/en/notebooks/#community-notebooks | .md | More notebooks developed by the community are available [here](https://hf.co/docs/transformers/community#community-notebooks). | 30_14_0 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/testing.md | https://huggingface.co/docs/transformers/en/testing/ | .md | <!--Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the | 31_0_0 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/testing.md | https://huggingface.co/docs/transformers/en/testing/ | .md | an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
rendered properly in your Markdown viewer.
--> | 31_0_1 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/testing.md | https://huggingface.co/docs/transformers/en/testing/#testing | .md | Let's take a look at how 🤗 Transformers models are tested and how you can write new tests and improve the existing ones.
There are 2 test suites in the repository:
1. `tests` -- tests for the general API
2. `examples` -- tests primarily for various applications that aren't part of the API | 31_1_0 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/testing.md | https://huggingface.co/docs/transformers/en/testing/#how-transformers-are-tested | .md | 1. Once a PR is submitted it gets tested with 9 CircleCi jobs. Every new commit to that PR gets retested. These jobs
are defined in this [config file](https://github.com/huggingface/transformers/tree/main/.circleci/config.yml), so that if needed you can reproduce the same
environment on your machine.
These CI jobs don't run `@slow` tests.
2. There are 3 jobs run by [github actions](https://github.com/huggingface/transformers/actions): | 31_2_0 |
/Users/nielsrogge/Documents/python_projecten/transformers/docs/source/en/testing.md | https://huggingface.co/docs/transformers/en/testing/#how-transformers-are-tested | .md | 2. There are 3 jobs run by [github actions](https://github.com/huggingface/transformers/actions):
- [torch hub integration](https://github.com/huggingface/transformers/tree/main/.github/workflows/github-torch-hub.yml): checks whether torch hub
integration works.
- [self-hosted (push)](https://github.com/huggingface/transformers/tree/main/.github/workflows/self-push.yml): runs fast tests on GPU only on commits on | 31_2_1 |
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