Documentation fixes (#20607)
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@@ -41,19 +41,19 @@ the hub already defines it:
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```python
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>>> pipe = pipeline(model="roberta-large-mnli")
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>>> pipe("This restaurant is awesome")
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[{'label': 'POSITIVE', 'score': 0.9998743534088135}]
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[{'label': 'NEUTRAL', 'score': 0.7313136458396912}]
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```
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To call a pipeline on many items, you can either call with a *list*.
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To call a pipeline on many items, you can call it with a *list*.
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```python
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>>> pipe = pipeline("text-classification")
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>>> pipe(["This restaurant is awesome", "This restaurant is aweful"])
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>>> pipe(["This restaurant is awesome", "This restaurant is awful"])
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[{'label': 'POSITIVE', 'score': 0.9998743534088135},
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{'label': 'NEGATIVE', 'score': 0.9996669292449951}]
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```
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To iterate of full datasets it is recommended to use a `dataset` directly. This means you don't need to allocate
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To iterate over full datasets it is recommended to use a `dataset` directly. This means you don't need to allocate
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the whole dataset at once, nor do you need to do batching yourself. This should work just as fast as custom loops on
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GPU. If it doesn't don't hesitate to create an issue.
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