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	<meta charset="utf-8" /><meta name="hf:doc:metadata" content="{"title":"دفاتر ملاحظات 🤗 Transformers","local":"دفاتر-ملاحظات--transformers","sections":[{"title":"دفاتر ملاحظات Hugging Face 🤗","local":"دفاتر-ملاحظات-hugging-face-","sections":[{"title":"دفاتر ملاحظات التوثيق","local":"دفاتر-ملاحظات-التوثيق","sections":[],"depth":3},{"title":"أمثلة PyTorch","local":"أمثلة-pytorch","sections":[{"title":"معالجة اللغة الطبيعية","local":"pytorch-nlp","sections":[],"depth":4},{"title":"رؤية الكمبيوتر","local":"pytorch-cv","sections":[],"depth":4},{"title":"الصوت","local":"pytorch-audio","sections":[],"depth":4},{"title":"التسلسلات البيولوجية","local":"pytorch-bio","sections":[],"depth":4},{"title":"طرائق أخرى","local":"pytorch-other","sections":[],"depth":4},{"title":"دفاتر ملاحظات الأدوات المساعدة","local":"pytorch-utility","sections":[],"depth":4}],"depth":3},{"title":"أمثلة TensorFlow","local":"أمثلة-tensorflow","sections":[{"title":"معالجة اللغة الطبيعية","local":"tensorflow-nlp","sections":[],"depth":4},{"title":"رؤية الكمبيوتر","local":"tensorflow-cv","sections":[],"depth":4},{"title":"التسلسلات البيولوجية","local":"tensorflow-bio","sections":[],"depth":4},{"title":"دفاتر ملاحظات الأدوات المساعدة","local":"tensorflow-utility","sections":[],"depth":4}],"depth":3},{"title":"دفاتر ملاحظات Optimum","local":"دفاتر-ملاحظات-optimum","sections":[],"depth":3}],"depth":2},{"title":"دفاتر ملاحظات المجتمع:","local":"دفاتر-ملاحظات-المجتمع","sections":[],"depth":2}],"depth":1}">
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	<link rel="modulepreload" href="/docs/transformers/pr_28250/ar/_app/immutable/chunks/EditOnGithub.98bf070f.js"><!-- HEAD_svelte-u9bgzb_START --><meta name="hf:doc:metadata" content="{"title":"دفاتر ملاحظات 🤗 Transformers","local":"دفاتر-ملاحظات--transformers","sections":[{"title":"دفاتر ملاحظات Hugging Face 🤗","local":"دفاتر-ملاحظات-hugging-face-","sections":[{"title":"دفاتر ملاحظات التوثيق","local":"دفاتر-ملاحظات-التوثيق","sections":[],"depth":3},{"title":"أمثلة PyTorch","local":"أمثلة-pytorch","sections":[{"title":"معالجة اللغة الطبيعية","local":"pytorch-nlp","sections":[],"depth":4},{"title":"رؤية الكمبيوتر","local":"pytorch-cv","sections":[],"depth":4},{"title":"الصوت","local":"pytorch-audio","sections":[],"depth":4},{"title":"التسلسلات البيولوجية","local":"pytorch-bio","sections":[],"depth":4},{"title":"طرائق أخرى","local":"pytorch-other","sections":[],"depth":4},{"title":"دفاتر ملاحظات الأدوات المساعدة","local":"pytorch-utility","sections":[],"depth":4}],"depth":3},{"title":"أمثلة TensorFlow","local":"أمثلة-tensorflow","sections":[{"title":"معالجة اللغة الطبيعية","local":"tensorflow-nlp","sections":[],"depth":4},{"title":"رؤية الكمبيوتر","local":"tensorflow-cv","sections":[],"depth":4},{"title":"التسلسلات البيولوجية","local":"tensorflow-bio","sections":[],"depth":4},{"title":"دفاتر ملاحظات الأدوات المساعدة","local":"tensorflow-utility","sections":[],"depth":4}],"depth":3},{"title":"دفاتر ملاحظات Optimum","local":"دفاتر-ملاحظات-optimum","sections":[],"depth":3}],"depth":2},{"title":"دفاتر ملاحظات المجتمع:","local":"دفاتر-ملاحظات-المجتمع","sections":[],"depth":2}],"depth":1}"><!-- HEAD_svelte-u9bgzb_END --> <p></p> <h1 class="relative group"><a id="دفاتر-ملاحظات--transformers" 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="#دفاتر-ملاحظات--transformers"><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>دفاتر ملاحظات 🤗 Transformers</span></h1> <p data-svelte-h="svelte-xrhdxr">يمكنك أن تجد هنا قائمة بدفاتر الملاحظات الرسمية التي تقدمها Hugging Face.</p> <p data-svelte-h="svelte-q7jp8p">كما نود أن ندرج هنا محتوى مثيرًا للاهتمام تم إنشاؤه بواسطة المجتمع.
	إذا كتبت دفتر ملاحظات يستفيد من 🤗 Transformers وتود إدراجه هنا، فيُرجى فتح طلب سحب حتى يمكن تضمينه ضمن دفاتر ملاحظات المجتمع.</p> <h2 class="relative group"><a id="دفاتر-ملاحظات-hugging-face-" 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="#دفاتر-ملاحظات-hugging-face-"><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>دفاتر ملاحظات Hugging Face 🤗</span></h2> <h3 class="relative group"><a id="دفاتر-ملاحظات-التوثيق" 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="#دفاتر-ملاحظات-التوثيق"><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>دفاتر ملاحظات التوثيق</span></h3> <p data-svelte-h="svelte-ph8lkb">يمكنك فتح أي صفحة من صفحات التوثيق كدفتر ملاحظات في Colab (يوجد زر مباشرة على تلك الصفحات) ولكنها مدرجة هنا أيضًا إذا كنت بحاجة إليها:</p> <table data-svelte-h="svelte-eboh42"><thead><tr><th align="left">دفتر الملاحظات</th> <th align="left">الوصف</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">جولة سريعة في المكتبة</a></td> <td align="left">عرض لمختلف واجهات برمجة التطبيقات في 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">ملخص المهام</a></td> <td align="left">كيفية تشغيل نماذج مكتبة Transformers مهمة تلو الأخرى</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">معالجة البيانات مسبقًا</a></td> <td align="left">كيفية استخدام محلل لغوي لمعالجة بياناتك مسبقًا</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">الضبط الدقيق لنموذج مُدرَّب مسبقًا</a></td> <td align="left">كيفية استخدام المدرب لضبط نموذج مُدرَّب مسبقًا بدقة</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">ملخص للمحللات اللغوية</a></td> <td align="left">الاختلافات بين خوارزمية المحلل اللغوي</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">النماذج متعددة اللغات</a></td> <td align="left">كيفية استخدام النماذج متعددة اللغات للمكتبة</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="أمثلة-pytorch" 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="#أمثلة-pytorch"><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>أمثلة PyTorch</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>معالجة اللغة الطبيعية</span></h4> <table data-svelte-h="svelte-zyp7xn"><thead><tr><th align="left">دفتر الملاحظات</th> <th align="left">الوصف</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">تدريب محللك اللغوي</a></td> <td align="left">كيفية تدريب واستخدام محللك اللغوي الخاص بك</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">تدريب نموذج لغتك</a></td> <td align="left">كيفية البدء بسهولة في استخدام المحولات</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">كيفية ضبط نموذج بدقة على تصنيف النص</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج مُدرَّب مسبقًا بدقة على أي مهمة GLUE.</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">كيفية ضبط نموذج بدقة على النمذجة اللغوية</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج مُدرَّب مسبقًا بدقة على مهمة LM سببية أو مقنعة.</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">كيفية ضبط نموذج بدقة على تصنيف الرموز المميزة</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج مُدرَّب مسبقًا بدقة على مهمة تصنيف الرموز المميزة (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">كيفية ضبط نموذج بدقة على الإجابة على الأسئلة</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج مُدرَّب مسبقًا بدقة على 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">كيفية ضبط نموذج بدقة على الاختيار من متعدد</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج مُدرَّب مسبقًا بدقة على 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">كيفية ضبط نموذج بدقة على الترجمة</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج مُدرَّب مسبقًا بدقة على 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">كيفية ضبط نموذج بدقة على التلخيص</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج مُدرَّب مسبقًا بدقة على 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">كيفية تدريب نموذج لغة من البداية</a></td> <td align="left">تسليط الضوء على جميع الخطوات لتدريب نموذج Transformer بشكل فعال على بيانات مخصصة</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">كيفية إنشاء نص</a></td> <td align="left">كيفية استخدام أساليب فك التشفير المختلفة لإنشاء اللغة باستخدام المحولات</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">كيفية إنشاء نص (مع قيود)</a></td> <td align="left">كيفية توجيه إنشاء اللغة باستخدام القيود التي يوفرها المستخدم</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">كيف يدفع Reformer حدود النمذجة اللغوية</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>رؤية الكمبيوتر</span></h4> <table data-svelte-h="svelte-19a8z4h"><thead><tr><th align="left">دفتر الملاحظات</th> <th align="left">الوصف</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">كيفية ضبط نموذج بدقة على تصنيف الصور (Torchvision)</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا باستخدام Torchvision وضبط أي نموذج رؤية مُدرَّب مسبقًا بدقة على تصنيف الصور</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">كيفية ضبط نموذج بدقة على تصنيف الصور (Albumentations)</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا باستخدام Albumentations وضبط أي نموذج رؤية مُدرَّب مسبقًا بدقة على تصنيف الصور</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">كيفية ضبط نموذج بدقة على تصنيف الصور (Kornia)</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا باستخدام Kornia وضبط أي نموذج رؤية مُدرَّب مسبقًا بدقة على تصنيف الصور</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">كيفية إجراء الكشف عن الأشياء بدون لقطات مع OWL-ViT</a></td> <td align="left">يوضح كيفية إجراء الكشف عن الأشياء بدون لقطات على الصور باستخدام استعلامات نصية</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">كيفية ضبط نموذج وصف الصور بدقة</a></td> <td align="left">يوضح كيفية ضبط BLIP بدقة لوصف الصور على مجموعة بيانات مخصصة</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">كيفية بناء نظام تشابه الصور مع Transformers</a></td> <td align="left">يوضح كيفية بناء نظام تشابه الصور</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">كيفية ضبط نموذج SegFormer بدقة على التجزئة الدلالية</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج SegFormer مُدرَّب مسبقًا بدقة على التجزئة الدلالية</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">كيفية ضبط نموذج VideoMAE بدقة على تصنيف الفيديو</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج VideoMAE مُدرَّب مسبقًا بدقة على تصنيف الفيديو</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>الصوت</span></h4> <table data-svelte-h="svelte-1c2owmy"><thead><tr><th align="left">دفتر الملاحظات</th> <th align="left">الوصف</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">كيفية ضبط نموذج التعرف على الكلام باللغة الإنجليزية بدقة</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج كلام مُدرَّب مسبقًا بدقة على 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">كيفية ضبط نموذج التعرف على الكلام بأي لغة بدقة</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج كلام مُدرَّب مسبقًا متعدد اللغات بدقة على 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">كيفية ضبط نموذج بدقة على تصنيف الصوت</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج كلام مُدرَّب مسبقًا بدقة على 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>التسلسلات البيولوجية</span></h4> <table data-svelte-h="svelte-eyhqgd"><thead><tr><th align="left">دفتر الملاحظات</th> <th align="left">الوصف</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">كيفية ضبط نموذج بروتين مُدرَّب مسبقًا بدقة</a></td> <td align="left">شاهد كيفية ترميز البروتينات وضبط نموذج “لغة” بروتين مُدرَّب مسبقًا كبير بدقة</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">كيفية إنشاء طيات بروتينية</a></td> <td align="left">شاهد كيفية الانتقال من تسلسل البروتين إلى نموذج بروتين كامل وملف PDB</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">كيفية ضبط نموذج محول النيوكليوتيدات بدقة</a></td> <td align="left">شاهد كيفية ترميز الحمض النووي وضبط نموذج “لغة” الحمض النووي مُدرَّب مسبقًا كبير بدقة</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">ضبط نموذج محول النيوكليوتيدات بدقة باستخدام LoRA</a></td> <td align="left">تدريب نماذج DNA أكبر بكثير بطريقة فعالة من حيث الذاكرة</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>طرائق أخرى</span></h4> <table data-svelte-h="svelte-ckad5i"><thead><tr><th align="left">دفتر الملاحظات</th> <th align="left">الوصف</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">التنبؤ الاحتمالي بالسلاسل الزمنية</a></td> <td align="left">شاهد كيفية تدريب Time Series Transformer على مجموعة بيانات مخصصة</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>دفاتر ملاحظات الأدوات المساعدة</span></h4> <table data-svelte-h="svelte-cu6fyq"><thead><tr><th align="left">دفتر الملاحظات</th> <th align="left">الوصف</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">كيفية تصدير النموذج إلى ONNX</a></td> <td align="left">تسليط الضوء على كيفية التصدير وتشغيل أعباء عمل الاستدلال من خلال 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">كيفية استخدام المعايير</a></td> <td align="left">كيفية قياس أداء النماذج باستخدام المحولات</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="أمثلة-tensorflow" 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="#أمثلة-tensorflow"><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>أمثلة TensorFlow</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>معالجة اللغة الطبيعية</span></h4> <table data-svelte-h="svelte-1t7s359"><thead><tr><th align="left">دفتر الملاحظات</th> <th align="left">الوصف</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">تدريب محللك اللغوي</a></td> <td align="left">كيفية تدريب واستخدام محللك اللغوي الخاص بك</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">تدريب نموذج لغتك</a></td> <td align="left">كيفية البدء بسهولة في استخدام المحولات</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">كيفية ضبط نموذج بدقة على تصنيف النص</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج مُدرَّب مسبقًا بدقة على أي مهمة GLUE.</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">كيفية ضبط نموذج بدقة على النمذجة اللغوية</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج مُدرَّب مسبقًا بدقة على مهمة LM سببية أو مقنعة.</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">كيفية ضبط نموذج بدقة على تصنيف الرموز المميزة</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج مُدرَّب مسبقًا بدقة على مهمة تصنيف الرموز المميزة (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">كيفية ضبط نموذج بدقة على الإجابة على الأسئلة</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج مُدرَّب مسبقًا بدقة على 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">كيفية ضبط نموذج بدقة على الاختيار من متعدد</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج مُدرَّب مسبقًا بدقة على 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">كيفية ضبط نموذج بدقة على الترجمة</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج مُدرَّب مسبقًا بدقة على 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">كيفية ضبط نموذج بدقة على التلخيص</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج مُدرَّب مسبقًا بدقة على 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>رؤية الكمبيوتر</span></h4> <table data-svelte-h="svelte-16uw4tz"><thead><tr><th align="left">دفتر الملاحظات</th> <th align="left">الوصف</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">كيفية ضبط نموذج بدقة على تصنيف الصور</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط أي نموذج رؤية مُدرَّب مسبقًا بدقة على تصنيف الصور</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">كيفية ضبط نموذج SegFormer بدقة على التجزئة الدلالية</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج SegFormer مُدرَّب مسبقًا بدقة على التجزئة الدلالية</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>التسلسلات البيولوجية</span></h4> <table data-svelte-h="svelte-3rffcr"><thead><tr><th align="left">دفتر الملاحظات</th> <th align="left">الوصف</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">كيفية ضبط نموذج بروتين مُدرَّب مسبقًا بدقة</a></td> <td align="left">شاهد كيفية ترميز البروتينات وضبط نموذج “لغة” بروتين مُدرَّب مسبقًا كبير بدقة</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>دفاتر ملاحظات الأدوات المساعدة</span></h4> <table data-svelte-h="svelte-16090es"><thead><tr><th align="left">دفتر الملاحظات</th> <th align="left">الوصف</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">كيفية تدريب نماذج TF/Keras على TPU</a></td> <td align="left">شاهد كيفية التدريب بسرعة عالية على أجهزة TPU من Google</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="دفاتر-ملاحظات-optimum" 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="#دفاتر-ملاحظات-optimum"><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>دفاتر ملاحظات Optimum</span></h3> <p data-svelte-h="svelte-r6th5u">🤗 <a href="https://github.com/huggingface/optimum" rel="nofollow">Optimum</a> هو امتداد لـ 🤗 Transformers، يوفر مجموعة من أدوات تحسين الأداء التي تمكن من تحقيق أقصى قدر من الكفاءة لتدريب وتشغيل النماذج على الأجهزة المستهدفة.</p> <table data-svelte-h="svelte-8uifm4"><thead><tr><th align="left">دفتر الملاحظات</th> <th align="left">الوصف</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">كيفية تكميم نموذج باستخدام ONNX Runtime لتصنيف النص</a></td> <td align="left">يوضح كيفية تطبيق التكميم الثابت والديناميكي على نموذج باستخدام <a href="https://github.com/microsoft/onnxruntime" rel="nofollow">ONNX Runtime</a> لأي مهمة GLUE.</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">كيفية تكميم نموذج باستخدام Intel Neural Compressor لتصنيف النص</a></td> <td align="left">يوضح كيفية تطبيق التكميم الثابت والديناميكي والتدريبي على نموذج باستخدام <a href="https://github.com/intel/neural-compressor" rel="nofollow">Intel Neural Compressor (INC)</a> لأي مهمة GLUE.</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">كيفية ضبط نموذج بدقة على تصنيف النص باستخدام ONNX Runtime</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج بدقة على أي مهمة GLUE باستخدام <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">كيفية ضبط نموذج بدقة على التلخيص باستخدام ONNX Runtime</a></td> <td align="left">يوضح كيفية معالجة البيانات مسبقًا وضبط نموذج بدقة على XSUM باستخدام <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="دفاتر-ملاحظات-المجتمع" 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="#دفاتر-ملاحظات-المجتمع"><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>دفاتر ملاحظات المجتمع:</span></h2> <p data-svelte-h="svelte-1ik8n7m">تتوفر المزيد من دفاتر الملاحظات التي طورها المجتمع <a href="https://hf.co/docs/transformers/community#community-notebooks" rel="nofollow">هنا</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/ar/notebooks.md" 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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