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Adding doctest for zero-shot-classification pipeline. #20268

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Narsil merged 2 commits into from
Nov 16, 2022
Merged

Adding doctest for zero-shot-classification pipeline. #20268

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42fb4c9
Adding doctest for `zero-shot-classification` pipeline.
Narsil Nov 16, 2022
e3351b6
Removing nested_simplify.
Narsil Nov 16, 2022
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25 changes: 24 additions & 1 deletion src/transformers/pipelines/zero_shot_classification.py
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Expand Up @@ -46,13 +46,36 @@ def __call__(self, sequences, labels, hypothesis_template):
class ZeroShotClassificationPipeline(ChunkPipeline):
"""
NLI-based zero-shot classification pipeline using a `ModelForSequenceClassification` trained on NLI (natural
language inference) tasks.
language inference) tasks. Equivalent of `text-classification` pipelines, but these models don't require a
hardcoded number of potential classes, they can be chosen at runtime. It usually means it's slower but it is
**much** more flexible.

Any combination of sequences and labels can be passed and each combination will be posed as a premise/hypothesis
pair and passed to the pretrained model. Then, the logit for *entailment* is taken as the logit for the candidate
label being valid. Any NLI model can be used, but the id of the *entailment* label must be included in the model
config's :attr:*~transformers.PretrainedConfig.label2id*.

Example:

```python
>>> from transformers import pipeline

>>> oracle = pipeline(model="facebook/bart-large-mnli")
>>> answers = oracle(
... "I have a problem with my iphone that needs to be resolved asap!!",
... candidate_labels=["urgent", "not urgent", "phone", "tablet", "computer"],
... )
{'sequence': 'I have a problem with my iphone that needs to be resolved asap!!', 'labels': ['urgent', 'phone', 'computer', 'not urgent', 'tablet'], 'scores': [0.504, 0.479, 0.013, 0.003, 0.002]}

>>> oracle(
... "I have a problem with my iphone that needs to be resolved asap!!",
... candidate_labels=["english", "german"],
... )
{'sequence': 'I have a problem with my iphone that needs to be resolved asap!!', 'labels': ['english', 'german'], 'scores': [0.814, 0.186]}
```

[Learn more about the basics of using a pipeline in the [pipeline tutorial]](../pipeline_tutorial)

This NLI pipeline can currently be loaded from [`pipeline`] using the following task identifier:
`"zero-shot-classification"`.

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