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<meta charset="utf-8" /><meta name="hf:doc:metadata" content="{&quot;title&quot;:&quot;🤗 Transformers Notebooks&quot;,&quot;local&quot;:&quot;-transformers-notebooks&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Hugging Face’s notebooks 🤗&quot;,&quot;local&quot;:&quot;hugging-faces-notebooks-&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Documentation notebooks&quot;,&quot;local&quot;:&quot;documentation-notebooks&quot;,&quot;sections&quot;:[],&quot;depth&quot;:3},{&quot;title&quot;:&quot;PyTorch Examples&quot;,&quot;local&quot;:&quot;pytorch-examples&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Natural Language Processing&quot;,&quot;local&quot;:&quot;pytorch-nlp&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Computer Vision&quot;,&quot;local&quot;:&quot;pytorch-cv&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Audio&quot;,&quot;local&quot;:&quot;pytorch-audio&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Biological Sequences&quot;,&quot;local&quot;:&quot;pytorch-bio&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Other modalities&quot;,&quot;local&quot;:&quot;pytorch-other&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Utility notebooks&quot;,&quot;local&quot;:&quot;pytorch-utility&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4}],&quot;depth&quot;:3},{&quot;title&quot;:&quot;TensorFlow Examples&quot;,&quot;local&quot;:&quot;tensorflow-examples&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Natural Language Processing&quot;,&quot;local&quot;:&quot;tensorflow-nlp&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Computer Vision&quot;,&quot;local&quot;:&quot;tensorflow-cv&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Biological Sequences&quot;,&quot;local&quot;:&quot;tensorflow-bio&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Utility notebooks&quot;,&quot;local&quot;:&quot;tensorflow-utility&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4}],&quot;depth&quot;:3},{&quot;title&quot;:&quot;Optimum notebooks&quot;,&quot;local&quot;:&quot;optimum-notebooks&quot;,&quot;sections&quot;:[],&quot;depth&quot;:3}],&quot;depth&quot;:2},{&quot;title&quot;:&quot;Community notebooks:&quot;,&quot;local&quot;:&quot;community-notebooks&quot;,&quot;sections&quot;:[],&quot;depth&quot;:2}],&quot;depth&quot;:1}">
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 <link rel="modulepreload" href="/docs/transformers/pr_33913/en/_app/immutable/chunks/EditOnGithub.91d95064.js"><!-- HEAD_svelte-u9bgzb_START --><meta name="hf:doc:metadata" content="{&quot;title&quot;:&quot;🤗 Transformers Notebooks&quot;,&quot;local&quot;:&quot;-transformers-notebooks&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Hugging Face’s notebooks 🤗&quot;,&quot;local&quot;:&quot;hugging-faces-notebooks-&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Documentation notebooks&quot;,&quot;local&quot;:&quot;documentation-notebooks&quot;,&quot;sections&quot;:[],&quot;depth&quot;:3},{&quot;title&quot;:&quot;PyTorch Examples&quot;,&quot;local&quot;:&quot;pytorch-examples&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Natural Language Processing&quot;,&quot;local&quot;:&quot;pytorch-nlp&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Computer Vision&quot;,&quot;local&quot;:&quot;pytorch-cv&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Audio&quot;,&quot;local&quot;:&quot;pytorch-audio&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Biological Sequences&quot;,&quot;local&quot;:&quot;pytorch-bio&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Other modalities&quot;,&quot;local&quot;:&quot;pytorch-other&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Utility notebooks&quot;,&quot;local&quot;:&quot;pytorch-utility&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4}],&quot;depth&quot;:3},{&quot;title&quot;:&quot;TensorFlow Examples&quot;,&quot;local&quot;:&quot;tensorflow-examples&quot;,&quot;sections&quot;:[{&quot;title&quot;:&quot;Natural Language Processing&quot;,&quot;local&quot;:&quot;tensorflow-nlp&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Computer Vision&quot;,&quot;local&quot;:&quot;tensorflow-cv&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Biological Sequences&quot;,&quot;local&quot;:&quot;tensorflow-bio&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4},{&quot;title&quot;:&quot;Utility notebooks&quot;,&quot;local&quot;:&quot;tensorflow-utility&quot;,&quot;sections&quot;:[],&quot;depth&quot;:4}],&quot;depth&quot;:3},{&quot;title&quot;:&quot;Optimum notebooks&quot;,&quot;local&quot;:&quot;optimum-notebooks&quot;,&quot;sections&quot;:[],&quot;depth&quot;:3}],&quot;depth&quot;:2},{&quot;title&quot;:&quot;Community notebooks:&quot;,&quot;local&quot;:&quot;community-notebooks&quot;,&quot;sections&quot;:[],&quot;depth&quot;:2}],&quot;depth&quot;:1}"><!-- HEAD_svelte-u9bgzb_END --> <p></p> <h1 class="relative group"><a id="-transformers-notebooks" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#-transformers-notebooks"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>🤗 Transformers Notebooks</span></h1> <p data-svelte-h="svelte-8lxll4">You can find here a list of the official notebooks provided by Hugging Face.</p> <p data-svelte-h="svelte-e3ib48">Also, we would like to list here interesting content created by the community.
If you wrote some notebook(s) leveraging 🤗 Transformers and would like to be listed here, please open a
Pull Request so it can be included under the Community notebooks.</p> <h2 class="relative group"><a id="hugging-faces-notebooks-" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#hugging-faces-notebooks-"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Hugging Face’s notebooks 🤗</span></h2> <h3 class="relative group"><a id="documentation-notebooks" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#documentation-notebooks"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Documentation notebooks</span></h3> <p data-svelte-h="svelte-ork269">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 them:</p> <table data-svelte-h="svelte-1tyddix"><thead><tr><th align="left">Notebook</th> <th align="left">Description</th> <th align="left"></th> <th align="right"></th></tr></thead> <tbody><tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/transformers_doc/en/quicktour.ipynb" rel="nofollow">Quicktour of the library</a></td> <td align="left">A presentation of the various APIs in Transformers</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/transformers_doc/en/quicktour.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/en/transformers_doc/quicktour.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/transformers_doc/en/task_summary.ipynb" rel="nofollow">Summary of the tasks</a></td> <td align="left">How to run the models of the Transformers library task by task</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/transformers_doc/en/task_summary.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/transformers_doc/en/task_summary.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/transformers_doc/en/preprocessing.ipynb" rel="nofollow">Preprocessing data</a></td> <td align="left">How to use a tokenizer to preprocess your data</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/transformers_doc/en/preprocessing.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/transformers_doc/en/preprocessing.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/transformers_doc/en/training.ipynb" rel="nofollow">Fine-tuning a pretrained model</a></td> <td align="left">How to use the Trainer to fine-tune a pretrained model</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/transformers_doc/en/training.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/transformers_doc/en/training.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/transformers_doc/en/tokenizer_summary.ipynb" rel="nofollow">Summary of the tokenizers</a></td> <td align="left">The differences between the tokenizers algorithm</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/transformers_doc/en/tokenizer_summary.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/transformers_doc/en/tokenizer_summary.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/transformers_doc/en/multilingual.ipynb" rel="nofollow">Multilingual models</a></td> <td align="left">How to use the multilingual models of the library</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/transformers_doc/en/multilingual.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/transformers_doc/en/multilingual.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr></tbody></table> <h3 class="relative group"><a id="pytorch-examples" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#pytorch-examples"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>PyTorch Examples</span></h3> <h4 class="relative group"><a id="pytorch-nlp" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#pytorch-nlp"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Natural Language Processing</span></h4> <table data-svelte-h="svelte-1p89anz"><thead><tr><th align="left">Notebook</th> <th align="left">Description</th> <th align="left"></th> <th align="right"></th></tr></thead> <tbody><tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/tokenizer_training.ipynb" rel="nofollow">Train your tokenizer</a></td> <td align="left">How to train and use your very own tokenizer</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/tokenizer_training.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/tokenizer_training.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/language_modeling_from_scratch.ipynb" rel="nofollow">Train your language model</a></td> <td align="left">How to easily start using transformers</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/language_modeling_from_scratch.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/language_modeling_from_scratch.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/text_classification.ipynb" rel="nofollow">How to fine-tune a model on text classification</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained model on any GLUE task.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/language_modeling.ipynb" rel="nofollow">How to fine-tune a model on language modeling</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained model on a causal or masked LM task.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/language_modeling.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/language_modeling.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/token_classification.ipynb" rel="nofollow">How to fine-tune a model on token classification</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained model on a token classification task (NER, PoS).</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/token_classification.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/token_classification.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/question_answering.ipynb" rel="nofollow">How to fine-tune a model on question answering</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained model on SQUAD.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/question_answering.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/question_answering.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/multiple_choice.ipynb" rel="nofollow">How to fine-tune a model on multiple choice</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained model on SWAG.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/multiple_choice.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/multiple_choice.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/translation.ipynb" rel="nofollow">How to fine-tune a model on translation</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained model on WMT.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/translation.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/translation.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/summarization.ipynb" rel="nofollow">How to fine-tune a model on summarization</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained model on XSUM.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/summarization.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/summarization.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/blog/blob/main/notebooks/01_how_to_train.ipynb" rel="nofollow">How to train a language model from scratch</a></td> <td align="left">Highlight all the steps to effectively train Transformer model on custom data</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/blog/blob/main/notebooks/01_how_to_train.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/blog/blob/main/notebooks/01_how_to_train.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/blog/blob/main/notebooks/02_how_to_generate.ipynb" rel="nofollow">How to generate text</a></td> <td align="left">How to use different decoding methods for language generation with transformers</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/blog/blob/main/notebooks/02_how_to_generate.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/blog/blob/main/notebooks/02_how_to_generate.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/blog/blob/main/notebooks/53_constrained_beam_search.ipynb" rel="nofollow">How to generate text (with constraints)</a></td> <td align="left">How to guide language generation with user-provided constraints</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/blog/blob/main/notebooks/53_constrained_beam_search.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/blog/blob/main/notebooks/53_constrained_beam_search.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/blog/blob/main/notebooks/03_reformer.ipynb" rel="nofollow">Reformer</a></td> <td align="left">How Reformer pushes the limits of language modeling</td> <td align="left"><a href="https://colab.research.google.com/github/patrickvonplaten/blog/blob/main/notebooks/03_reformer.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/patrickvonplaten/blog/blob/main/notebooks/03_reformer.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr></tbody></table> <h4 class="relative group"><a id="pytorch-cv" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#pytorch-cv"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Computer Vision</span></h4> <table data-svelte-h="svelte-1jqc5b3"><thead><tr><th align="left">Notebook</th> <th align="left">Description</th> <th align="left"></th> <th align="right"></th></tr></thead> <tbody><tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/image_classification.ipynb" rel="nofollow">How to fine-tune a model on image classification (Torchvision)</a></td> <td align="left">Show how to preprocess the data using Torchvision and fine-tune any pretrained Vision model on Image Classification</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/image_classification_albumentations.ipynb" rel="nofollow">How to fine-tune a model on image classification (Albumentations)</a></td> <td align="left">Show how to preprocess the data using Albumentations and fine-tune any pretrained Vision model on Image Classification</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification_albumentations.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/image_classification_albumentations.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/image_classification_kornia.ipynb" rel="nofollow">How to fine-tune a model on image classification (Kornia)</a></td> <td align="left">Show how to preprocess the data using Kornia and fine-tune any pretrained Vision model on Image Classification</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification_kornia.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/image_classification_kornia.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/zeroshot_object_detection_with_owlvit.ipynb" rel="nofollow">How to perform zero-shot object detection with OWL-ViT</a></td> <td align="left">Show how to perform zero-shot object detection on images with text queries</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/zeroshot_object_detection_with_owlvit.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/zeroshot_object_detection_with_owlvit.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/image_captioning_blip.ipynb" rel="nofollow">How to fine-tune an image captioning model</a></td> <td align="left">Show how to fine-tune BLIP for image captioning on a custom dataset</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_captioning_blip.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/image_captioning_blip.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/image_similarity.ipynb" rel="nofollow">How to build an image similarity system with Transformers</a></td> <td align="left">Show how to build an image similarity system</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_similarity.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/image_similarity.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/semantic_segmentation.ipynb" rel="nofollow">How to fine-tune a SegFormer model on semantic segmentation</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained SegFormer model on Semantic Segmentation</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/semantic_segmentation.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/semantic_segmentation.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/video_classification.ipynb" rel="nofollow">How to fine-tune a VideoMAE model on video classification</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained VideoMAE model on Video Classification</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/video_classification.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/video_classification.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr></tbody></table> <h4 class="relative group"><a id="pytorch-audio" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#pytorch-audio"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Audio</span></h4> <table data-svelte-h="svelte-17b171l"><thead><tr><th align="left">Notebook</th> <th align="left">Description</th> <th align="left"></th> <th align="right"></th></tr></thead> <tbody><tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/speech_recognition.ipynb" rel="nofollow">How to fine-tune a speech recognition model in English</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained Speech model on TIMIT</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/speech_recognition.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/speech_recognition.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/multi_lingual_speech_recognition.ipynb" rel="nofollow">How to fine-tune a speech recognition model in any language</a></td> <td align="left">Show how to preprocess the data and fine-tune a multi-lingually pretrained speech model on Common Voice</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/multi_lingual_speech_recognition.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/multi_lingual_speech_recognition.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/audio_classification.ipynb" rel="nofollow">How to fine-tune a model on audio classification</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained Speech model on Keyword Spotting</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/audio_classification.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/audio_classification.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr></tbody></table> <h4 class="relative group"><a id="pytorch-bio" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#pytorch-bio"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Biological Sequences</span></h4> <table data-svelte-h="svelte-1jgw32m"><thead><tr><th align="left">Notebook</th> <th align="left">Description</th> <th align="left"></th> <th align="right"></th></tr></thead> <tbody><tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/protein_language_modeling.ipynb" rel="nofollow">How to fine-tune a pre-trained protein model</a></td> <td align="left">See how to tokenize proteins and fine-tune a large pre-trained protein “language” model</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/protein_language_modeling.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/protein_language_modeling.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/protein_folding.ipynb" rel="nofollow">How to generate protein folds</a></td> <td align="left">See how to go from protein sequence to a full protein model and PDB file</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/protein_folding.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/protein_folding.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/nucleotide_transformer_dna_sequence_modelling.ipynb" rel="nofollow">How to fine-tune a Nucleotide Transformer model</a></td> <td align="left">See how to tokenize DNA and fine-tune a large pre-trained DNA “language” model</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/nucleotide_transformer_dna_sequence_modelling.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/nucleotide_transformer_dna_sequence_modelling.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/nucleotide_transformer_dna_sequence_modelling_with_peft.ipynb" rel="nofollow">Fine-tune a Nucleotide Transformer model with LoRA</a></td> <td align="left">Train even larger DNA models in a memory-efficient way</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/nucleotide_transformer_dna_sequence_modelling_with_peft.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/nucleotide_transformer_dna_sequence_modelling_with_peft.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr></tbody></table> <h4 class="relative group"><a id="pytorch-other" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#pytorch-other"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Other modalities</span></h4> <table data-svelte-h="svelte-t0yh3g"><thead><tr><th align="left">Notebook</th> <th align="left">Description</th> <th align="left"></th> <th align="right"></th></tr></thead> <tbody><tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/time-series-transformers.ipynb" rel="nofollow">Probabilistic Time Series Forecasting</a></td> <td align="left">See how to train Time Series Transformer on a custom dataset</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/time-series-transformers.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/time-series-transformers.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr></tbody></table> <h4 class="relative group"><a id="pytorch-utility" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#pytorch-utility"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Utility notebooks</span></h4> <table data-svelte-h="svelte-1266zka"><thead><tr><th align="left">Notebook</th> <th align="left">Description</th> <th align="left"></th> <th align="right"></th></tr></thead> <tbody><tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/onnx-export.ipynb" rel="nofollow">How to export model to ONNX</a></td> <td align="left">Highlight how to export and run inference workloads through ONNX</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/onnx-export.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/onnx-export.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/benchmark.ipynb" rel="nofollow">How to use Benchmarks</a></td> <td align="left">How to benchmark models with transformers</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/benchmark.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/benchmark.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr></tbody></table> <h3 class="relative group"><a id="tensorflow-examples" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#tensorflow-examples"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>TensorFlow Examples</span></h3> <h4 class="relative group"><a id="tensorflow-nlp" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#tensorflow-nlp"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Natural Language Processing</span></h4> <table data-svelte-h="svelte-kioj2r"><thead><tr><th align="left">Notebook</th> <th align="left">Description</th> <th align="left"></th> <th align="right"></th></tr></thead> <tbody><tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/tokenizer_training.ipynb" rel="nofollow">Train your tokenizer</a></td> <td align="left">How to train and use your very own tokenizer</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/tokenizer_training.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/tokenizer_training.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/language_modeling_from_scratch-tf.ipynb" rel="nofollow">Train your language model</a></td> <td align="left">How to easily start using transformers</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/language_modeling_from_scratch-tf.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/language_modeling_from_scratch-tf.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/text_classification-tf.ipynb" rel="nofollow">How to fine-tune a model on text classification</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained model on any GLUE task.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification-tf.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification-tf.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/language_modeling-tf.ipynb" rel="nofollow">How to fine-tune a model on language modeling</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained model on a causal or masked LM task.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/language_modeling-tf.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/language_modeling-tf.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/token_classification-tf.ipynb" rel="nofollow">How to fine-tune a model on token classification</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained model on a token classification task (NER, PoS).</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/token_classification-tf.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/token_classification-tf.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/question_answering-tf.ipynb" rel="nofollow">How to fine-tune a model on question answering</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained model on SQUAD.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/question_answering-tf.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/question_answering-tf.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/multiple_choice-tf.ipynb" rel="nofollow">How to fine-tune a model on multiple choice</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained model on SWAG.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/multiple_choice-tf.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/multiple_choice-tf.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/translation-tf.ipynb" rel="nofollow">How to fine-tune a model on translation</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained model on WMT.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/translation-tf.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/translation-tf.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/summarization-tf.ipynb" rel="nofollow">How to fine-tune a model on summarization</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained model on XSUM.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/summarization-tf.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/summarization-tf.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr></tbody></table> <h4 class="relative group"><a id="tensorflow-cv" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#tensorflow-cv"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Computer Vision</span></h4> <table data-svelte-h="svelte-5d4q41"><thead><tr><th align="left">Notebook</th> <th align="left">Description</th> <th align="left"></th> <th align="right"></th></tr></thead> <tbody><tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/image_classification-tf.ipynb" rel="nofollow">How to fine-tune a model on image classification</a></td> <td align="left">Show how to preprocess the data and fine-tune any pretrained Vision model on Image Classification</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification-tf.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/image_classification-tf.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/semantic_segmentation-tf.ipynb" rel="nofollow">How to fine-tune a SegFormer model on semantic segmentation</a></td> <td align="left">Show how to preprocess the data and fine-tune a pretrained SegFormer model on Semantic Segmentation</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/semantic_segmentation-tf.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/semantic_segmentation-tf.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr></tbody></table> <h4 class="relative group"><a id="tensorflow-bio" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#tensorflow-bio"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Biological Sequences</span></h4> <table data-svelte-h="svelte-1eggudk"><thead><tr><th align="left">Notebook</th> <th align="left">Description</th> <th align="left"></th> <th align="right"></th></tr></thead> <tbody><tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/protein_language_modeling-tf.ipynb" rel="nofollow">How to fine-tune a pre-trained protein model</a></td> <td align="left">See how to tokenize proteins and fine-tune a large pre-trained protein “language” model</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/protein_language_modeling-tf.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/protein_language_modeling-tf.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr></tbody></table> <h4 class="relative group"><a id="tensorflow-utility" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#tensorflow-utility"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Utility notebooks</span></h4> <table data-svelte-h="svelte-10jppcc"><thead><tr><th align="left">Notebook</th> <th align="left">Description</th> <th align="left"></th> <th align="right"></th></tr></thead> <tbody><tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/tpu_training-tf.ipynb" rel="nofollow">How to train TF/Keras models on TPU</a></td> <td align="left">See how to train at high speed on Google’s TPU hardware</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/tpu_training-tf.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/tpu_training-tf.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr></tbody></table> <h3 class="relative group"><a id="optimum-notebooks" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#optimum-notebooks"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Optimum notebooks</span></h3> <p data-svelte-h="svelte-psw519">🤗 <a href="https://github.com/huggingface/optimum" rel="nofollow">Optimum</a> is an extension of 🤗 Transformers, providing a set of performance optimization tools enabling maximum efficiency to train and run models on targeted hardwares.</p> <table data-svelte-h="svelte-1dquiwf"><thead><tr><th align="left">Notebook</th> <th align="left">Description</th> <th align="left"></th> <th align="right"></th></tr></thead> <tbody><tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/text_classification_quantization_ort.ipynb" rel="nofollow">How to quantize a model with ONNX Runtime for text classification</a></td> <td align="left">Show how to apply static and dynamic quantization on a model using <a href="https://github.com/microsoft/onnxruntime" rel="nofollow">ONNX Runtime</a> for any GLUE task.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_ort.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_ort.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb" rel="nofollow">How to quantize a model with Intel Neural Compressor for text classification</a></td> <td align="left">Show how to apply static, dynamic and aware training quantization on a model using <a href="https://github.com/intel/neural-compressor" rel="nofollow">Intel Neural Compressor (INC)</a> for any GLUE task.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/text_classification_ort.ipynb" rel="nofollow">How to fine-tune a model on text classification with ONNX Runtime</a></td> <td align="left">Show how to preprocess the data and fine-tune a model on any GLUE task using <a href="https://github.com/microsoft/onnxruntime" rel="nofollow">ONNX Runtime</a>.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification_ort.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification_ort.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr> <tr><td align="left"><a href="https://github.com/huggingface/notebooks/blob/main/examples/summarization_ort.ipynb" rel="nofollow">How to fine-tune a model on summarization with ONNX Runtime</a></td> <td align="left">Show how to preprocess the data and fine-tune a model on XSUM using <a href="https://github.com/microsoft/onnxruntime" rel="nofollow">ONNX Runtime</a>.</td> <td align="left"><a href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/summarization_ort.ipynb" rel="nofollow"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open in Colab"></a></td> <td align="right"><a href="https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/summarization_ort.ipynb" rel="nofollow"><img src="https://studiolab.sagemaker.aws/studiolab.svg" alt="Open in AWS Studio"></a></td></tr></tbody></table> <h2 class="relative group"><a id="community-notebooks" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#community-notebooks"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>Community notebooks:</span></h2> <p data-svelte-h="svelte-9qre29">More notebooks developed by the community are available <a href="https://hf.co/docs/transformers/community#community-notebooks" rel="nofollow">here</a>.</p> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/transformers/blob/main/docs/source/en/notebooks.md" target="_blank"><span data-svelte-h="svelte-1kd6by1">&lt;</span> <span data-svelte-h="svelte-x0xyl0">&gt;</span> <span data-svelte-h="svelte-1dajgef"><span class="underline ml-1.5">Update</span> on GitHub</span></a> <p></p>
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