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Fix typos in translated quicktour docs (#35302)

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* fix: quicktour typos

* fix: one more
This commit is contained in:
Jacky Lee
2024-12-17 09:32:00 -08:00
committed by GitHub
parent deac971c46
commit 4302b27719
9 changed files with 47 additions and 47 deletions
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docs/source/it/quicktour.md
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@@ -111,7 +111,7 @@ etichetta: negative, con punteggio: 0.9998
La [`pipeline`] può anche iterare su un dataset intero. Inizia installando la libreria [🤗 Datasets](https://huggingface.co/docs/datasets/):
```bash
pip install datasets
pip install datasets
```
Crea una [`pipeline`] con il compito che vuoi risolvere e con il modello che vuoi utilizzare.
@@ -385,8 +385,8 @@ Una caratteristica particolarmente interessante di 🤗 Transformers è la sua a
```py
>>> from transformers import AutoModel
>>> tokenizer = AutoTokenizer.from_pretrained(tf_save_directory)
>>> pt_model = AutoModelForSequenceClassification.from_pretrained(tf_save_directory, from_tf=True)
>>> tokenizer = AutoTokenizer.from_pretrained(pt_save_directory)
>>> pt_model = AutoModelForSequenceClassification.from_pretrained(pt_save_directory, from_pt=True)
```
</pt>
<tf>
@@ -394,8 +394,8 @@ Una caratteristica particolarmente interessante di 🤗 Transformers è la sua a
```py
>>> from transformers import TFAutoModel
>>> tokenizer = AutoTokenizer.from_pretrained(pt_save_directory)
>>> tf_model = TFAutoModelForSequenceClassification.from_pretrained(pt_save_directory, from_pt=True)
>>> tokenizer = AutoTokenizer.from_pretrained(tf_save_directory)
>>> tf_model = TFAutoModelForSequenceClassification.from_pretrained(tf_save_directory, from_tf=True)
```
</tf>
</frameworkcontent>