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Helpful tip #700

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3 changes: 3 additions & 0 deletions chapters/de/chapter3/2.mdx
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Expand Up @@ -87,6 +87,9 @@ In diesem Abschnitt verwenden wir den MRPC-Datensatz (Microsoft Research Paraphr
Das Hub enthält nicht nur Modelle; Es hat auch mehrere Datensätze in vielen verschiedenen Sprachen. Du kannst die Datensätze [hier](https://huggingface.co/datasets) durchsuchen, und wir empfehlen, einen weiteren Datensatz zu laden und zu verarbeiten, sobald Sie diesen Abschnitt abgeschlossen haben (die Dokumentation befindet sich [hier](https://huggingface.co/docs/datasets/loading)). Aber jetzt konzentrieren wir uns auf den MRPC-Datensatz! Dies ist einer der 10 Datensätze, aus denen sich das [GLUE-Benchmark](https://gluebenchmark.com/) zusammensetzt. Dies ist ein akademisches Benchmark, das verwendet wird, um die Performance von ML-Modellen in 10 verschiedenen Textklassifizierungsaufgaben zu messen.

Die Bibliothek 🤗 Datasets bietet einen leichten Befehl zum Herunterladen und Caching eines Datensatzes aus dem Hub. Wir können den MRPC-Datensatz wie folgt herunterladen:
<Tipp>
⚠️ ** Warnung** Stelle sicher, dass `datasets` installiert ist, indem du `pip install datasets` ausführst. Dann lade den MRPC-Datensatz und drucke ihn aus, um zu sehen, was er enthält.
</Tipp>

```py
from datasets import load_dataset
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4 changes: 4 additions & 0 deletions chapters/en/chapter3/2.mdx
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Expand Up @@ -88,6 +88,10 @@ The Hub doesn't just contain models; it also has multiple datasets in lots of di

The 🤗 Datasets library provides a very simple command to download and cache a dataset on the Hub. We can download the MRPC dataset like this:

<Tip>
⚠️ **Warning** Make sure that `datasets` is installed by running `pip install datasets`. Then, load the MRPC dataset and print it to see what it contains.
</Tip>

```py
from datasets import load_dataset

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4 changes: 4 additions & 0 deletions chapters/es/chapter3/2.mdx
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Expand Up @@ -91,6 +91,10 @@ El Hub no solo contiene modelos; sino que también tiene múltiples conjunto de

La librería 🤗 Datasets provee un comando muy simple para descargar y memorizar un conjunto de datos en el Hub. Podemos descargar el conjunto de datos de la siguiente manera:

<Tip>
⚠️ **Advertencia** Asegúrate de que `datasets` esté instalado ejecutando `pip install datasets`. Luego, carga el conjunto de datos MRPC y imprímelo para ver qué contiene.
</Tip>

```py
from datasets import load_dataset

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3 changes: 3 additions & 0 deletions chapters/fa/chapter3/2.mdx
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Expand Up @@ -105,6 +105,9 @@ model.train_on_batch(batch, labels)

<div dir="ltr">

<Tip>
⚠️ **هشدار** مطمئن شوید که `datasets` نصب شده است. برای اطمینان، دستور `pip install datasets` را اجرا کنید. سپس، مجموعه داده MRPC را بارگذاری کنید و آن را چاپ کنید تا ببینید چه چیزی در آن وجود دارد.
</Tip>
```py
from datasets import load_dataset

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4 changes: 4 additions & 0 deletions chapters/fr/chapter3/2.mdx
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Expand Up @@ -96,6 +96,10 @@ Le *Hub* ne contient pas seulement des modèles mais aussi plusieurs jeux de don

La bibliothèque 🤗 *Datasets* propose une commande très simple pour télécharger et mettre en cache un jeu de données à partir du *Hub*. On peut télécharger le jeu de données MRPC comme ceci :

<Tip>
⚠️ **Attention** Assurez-vous que `datasets` est installé en exécutant `pip install datasets`. Ensuite, chargez le jeu de données MRPC et imprimez-le pour voir ce qu'il contient.
</Tip>

```py
from datasets import load_dataset

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4 changes: 4 additions & 0 deletions chapters/hi/chapter3/2.mdx
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Expand Up @@ -88,6 +88,10 @@ model.train_on_batch(batch, labels)

🤗 डेटासेट लाइब्रेरी एक बहुत ही सरल कमांड प्रदान करती है हब पर डेटासेट को डाउनलोड और कैश करने के लिए। हम MRPC डेटासेट को इस तरह डाउनलोड कर सकते हैं:

<Tip>
⚠️ **चेतावनी** सुनिश्चित करें कि `datasets` स्थापित है। इसके लिए `pip install datasets` चलाएँ। फिर, MRPC डेटासेट को लोड करें और देखें कि इसमें क्या है।
</Tip>

```py
from datasets import load_dataset

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4 changes: 4 additions & 0 deletions chapters/it/chapter3/2.mdx
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Expand Up @@ -88,6 +88,10 @@ L'Hub non contiene solo modelli; contiene anche molti dataset in tante lingue di

La libreria 🤗 Datasets fornisce un comando molto semplice per scaricare e mettere nella cache un dataset sull'Hub. Il dataset MRPC può essere scaricato così:

<Tip>
⚠️ **Attenzione** Assicurati che `datasets` sia installato eseguendo `pip install datasets`. Poi, carica il dataset MRPC e stampalo per vedere cosa contiene.
</Tip>

```py
from datasets import load_dataset

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4 changes: 4 additions & 0 deletions chapters/ru/chapter3/2.mdx
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Expand Up @@ -88,6 +88,10 @@ Hub содержит не только модели, там также расп

Библиотека 🤗 Datasets предоставляет возможность использовать очень простую команду для загрузки и кэширования датасета с Hub. Мы можем загрузить датасет следующим образом:

<Tip>
⚠️ **Предупреждение** Убедитесь, что `datasets` установлены, выполнив `pip install datasets`. Затем загрузите набор данных MRPC и выведите его, чтобы увидеть, что он содержит.
</Tip>

```py
from datasets import load_dataset

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4 changes: 4 additions & 0 deletions chapters/th/chapter3/2.mdx
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Expand Up @@ -88,6 +88,10 @@ Hub นั้นไม่ได้เก็บเพียงแค่โมเ

ไลบรารี่ 🤗 Datasets library มีคำสั่งที่ใช้งานได้ง่ายมากในการดาวโหลดและ cache ชุดข้อมูลที่อยู่บน Hub เราสามารถดาวโหลดชุดข้อมูล MRPC ได้ดังนี้:

<Tip>
⚠️ **คำเตือน** ตรวจสอบให้แน่ใจว่า `datasets` ได้ถูกติดตั้งโดยการรัน `pip install datasets` ก่อน จากนั้นโหลดชุดข้อมูล MRPC และพิมพ์เพื่อดูว่ามีอะไรบ้าง
</Tip>

```py
from datasets import load_dataset

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