Buckets:
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| <link rel="modulepreload" href="/docs/tokenizers/pr_1605/en/_app/immutable/chunks/EditOnGithub.6d5e7de4.js"><!-- HEAD_svelte-u9bgzb_START --><meta name="hf:doc:metadata" content="{"title":"Training from memory","local":"training-from-memory","sections":[{"title":"The most basic way","local":"the-most-basic-way","sections":[],"depth":2},{"title":"Using the 🤗 Datasets library","local":"using-the--datasets-library","sections":[],"depth":2},{"title":"Using gzip files","local":"using-gzip-files","sections":[],"depth":2}],"depth":1}"><!-- HEAD_svelte-u9bgzb_END --> <p></p> <h1 class="relative group"><a id="training-from-memory" 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="#training-from-memory"><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>Training from memory</span></h1> <p data-svelte-h="svelte-zs4zcn">In the <a href="quicktour">Quicktour</a>, we saw how to build and train a | |
| tokenizer using text files, but we can actually use any Python Iterator. | |
| In this section we’ll see a few different ways of training our | |
| tokenizer.</p> <p data-svelte-h="svelte-1emvxpf">For all the examples listed below, we’ll use the same <a href="/docs/tokenizers/pr_1605/en/api/tokenizer#tokenizers.Tokenizer">Tokenizer</a> and | |
| <code>Trainer</code>, built as | |
| following:</p> <div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-keyword">from</span> tokenizers <span class="hljs-keyword">import</span> Tokenizer, decoders, models, normalizers, pre_tokenizers, trainers | |
| tokenizer = Tokenizer(models.Unigram()) | |
| tokenizer.normalizer = normalizers.NFKC() | |
| tokenizer.pre_tokenizer = pre_tokenizers.ByteLevel() | |
| tokenizer.decoder = decoders.ByteLevel() | |
| trainer = trainers.UnigramTrainer( | |
| vocab_size=<span class="hljs-number">20000</span>, | |
| initial_alphabet=pre_tokenizers.ByteLevel.alphabet(), | |
| special_tokens=[<span class="hljs-string">"<PAD>"</span>, <span class="hljs-string">"<BOS>"</span>, <span class="hljs-string">"<EOS>"</span>], | |
| )<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-jew2xy">This tokenizer is based on the <a href="/docs/tokenizers/pr_1605/en/api/models#tokenizers.models.Unigram">Unigram</a> model. It | |
| takes care of normalizing the input using the NFKC Unicode normalization | |
| method, and uses a <a href="/docs/tokenizers/pr_1605/en/api/pre-tokenizers#tokenizers.pre_tokenizers.ByteLevel">ByteLevel</a> pre-tokenizer with the corresponding decoder.</p> <p data-svelte-h="svelte-1cm91fx">For more information on the components used here, you can check | |
| <a href="components">here</a>.</p> <h2 class="relative group"><a id="the-most-basic-way" 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="#the-most-basic-way"><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>The most basic way</span></h2> <p data-svelte-h="svelte-800zef">As you probably guessed already, the easiest way to train our tokenizer | |
| is by using a <code>List</code>{.interpreted-text role=“obj”}:</p> <div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-comment"># First few lines of the "Zen of Python" https://www.python.org/dev/peps/pep-0020/</span> | |
| data = [ | |
| <span class="hljs-string">"Beautiful is better than ugly."</span> | |
| <span class="hljs-string">"Explicit is better than implicit."</span> | |
| <span class="hljs-string">"Simple is better than complex."</span> | |
| <span class="hljs-string">"Complex is better than complicated."</span> | |
| <span class="hljs-string">"Flat is better than nested."</span> | |
| <span class="hljs-string">"Sparse is better than dense."</span> | |
| <span class="hljs-string">"Readability counts."</span> | |
| ] | |
| tokenizer.train_from_iterator(data, trainer=trainer)<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-2k2g93">Easy, right? You can use anything working as an iterator here, be it a | |
| <code>List</code>{.interpreted-text role=“obj”}, <code>Tuple</code>{.interpreted-text | |
| role=“obj”}, or a <code>np.Array</code>{.interpreted-text role=“obj”}. Anything | |
| works as long as it provides strings.</p> <h2 class="relative group"><a id="using-the--datasets-library" 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="#using-the--datasets-library"><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>Using the 🤗 Datasets library</span></h2> <p data-svelte-h="svelte-tt7so">An awesome way to access one of the many datasets that exist out there | |
| is by using the 🤗 Datasets library. For more information about it, you | |
| should check <a href="https://huggingface.co/docs/datasets/" rel="nofollow">the official documentation | |
| here</a>.</p> <p data-svelte-h="svelte-8j5br2">Let’s start by loading our dataset:</p> <div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-keyword">import</span> datasets | |
| dataset = datasets.load_dataset(<span class="hljs-string">"wikitext"</span>, <span class="hljs-string">"wikitext-103-raw-v1"</span>, split=<span class="hljs-string">"train+test+validation"</span>)<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-134xe8u">The next step is to build an iterator over this dataset. The easiest way | |
| to do this is probably by using a generator:</p> <div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-keyword">def</span> <span class="hljs-title function_">batch_iterator</span>(<span class="hljs-params">batch_size=<span class="hljs-number">1000</span></span>): | |
| <span class="hljs-comment"># Only keep the text column to avoid decoding the rest of the columns unnecessarily</span> | |
| tok_dataset = dataset.select_columns(<span class="hljs-string">"text"</span>) | |
| <span class="hljs-keyword">for</span> batch <span class="hljs-keyword">in</span> tok_dataset.<span class="hljs-built_in">iter</span>(batch_size): | |
| <span class="hljs-keyword">yield</span> batch[<span class="hljs-string">"text"</span>]<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-18jpyth">As you can see here, for improved efficiency we can actually provide a | |
| batch of examples used to train, instead of iterating over them one by | |
| one. By doing so, we can expect performances very similar to those we | |
| got while training directly from files.</p> <p data-svelte-h="svelte-1ha2c1s">With our iterator ready, we just need to launch the training. In order | |
| to improve the look of our progress bars, we can specify the total | |
| length of the dataset:</p> <div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START -->tokenizer.train_from_iterator(batch_iterator(), trainer=trainer, length=<span class="hljs-built_in">len</span>(dataset))<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-9wooxy">And that’s it!</p> <h2 class="relative group"><a id="using-gzip-files" 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="#using-gzip-files"><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>Using gzip files</span></h2> <p data-svelte-h="svelte-rvsukz">Since gzip files in Python can be used as iterators, it is extremely | |
| simple to train on such files:</p> <div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="hljs-keyword">import</span> gzip | |
| <span class="hljs-keyword">with</span> gzip.<span class="hljs-built_in">open</span>(<span class="hljs-string">"data/my-file.0.gz"</span>, <span class="hljs-string">"rt"</span>) <span class="hljs-keyword">as</span> f: | |
| tokenizer.train_from_iterator(f, trainer=trainer)<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-1g7s20h">Now if we wanted to train from multiple gzip files, it wouldn’t be much | |
| harder:</p> <div class="code-block relative"><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START -->files = [<span class="hljs-string">"data/my-file.0.gz"</span>, <span class="hljs-string">"data/my-file.1.gz"</span>, <span class="hljs-string">"data/my-file.2.gz"</span>] | |
| <span class="hljs-keyword">def</span> <span class="hljs-title function_">gzip_iterator</span>(): | |
| <span class="hljs-keyword">for</span> path <span class="hljs-keyword">in</span> files: | |
| <span class="hljs-keyword">with</span> gzip.<span class="hljs-built_in">open</span>(path, <span class="hljs-string">"rt"</span>) <span class="hljs-keyword">as</span> f: | |
| <span class="hljs-keyword">for</span> line <span class="hljs-keyword">in</span> f: | |
| <span class="hljs-keyword">yield</span> line | |
| tokenizer.train_from_iterator(gzip_iterator(), trainer=trainer)<!-- HTML_TAG_END --></pre></div> <p data-svelte-h="svelte-15ag4ju">And voilà!</p> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/tokenizers/blob/main/docs/source-doc-builder/training_from_memory.mdx" target="_blank"><span data-svelte-h="svelte-1kd6by1"><</span> <span data-svelte-h="svelte-x0xyl0">></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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