diff --git a/src/transformers/pipelines/__init__.py b/src/transformers/pipelines/__init__.py index 1beda27ce88c..49242cfb12ec 100755 --- a/src/transformers/pipelines/__init__.py +++ b/src/transformers/pipelines/__init__.py @@ -590,15 +590,17 @@ def pipeline( >>> from transformers import pipeline, AutoModelForTokenClassification, AutoTokenizer >>> # Sentiment analysis pipeline - >>> pipeline("sentiment-analysis") + >>> analyzer = pipeline("sentiment-analysis") >>> # Question answering pipeline, specifying the checkpoint identifier - >>> pipeline("question-answering", model="distilbert-base-cased-distilled-squad", tokenizer="bert-base-cased") + >>> oracle = pipeline( + ... "question-answering", model="distilbert-base-cased-distilled-squad", tokenizer="bert-base-cased" + ... ) >>> # Named entity recognition pipeline, passing in a specific model and tokenizer >>> model = AutoModelForTokenClassification.from_pretrained("dbmdz/bert-large-cased-finetuned-conll03-english") >>> tokenizer = AutoTokenizer.from_pretrained("bert-base-cased") - >>> pipeline("ner", model=model, tokenizer=tokenizer) + >>> recognizer = pipeline("ner", model=model, tokenizer=tokenizer) ```""" if model_kwargs is None: model_kwargs = {} diff --git a/src/transformers/pipelines/document_question_answering.py b/src/transformers/pipelines/document_question_answering.py index 860702e08d5d..ce1c129b9a8b 100644 --- a/src/transformers/pipelines/document_question_answering.py +++ b/src/transformers/pipelines/document_question_answering.py @@ -112,12 +112,11 @@ class DocumentQuestionAnsweringPipeline(ChunkPipeline): >>> from transformers import pipeline >>> document_qa = pipeline(model="impira/layoutlm-document-qa") - >>> result = document_qa( + >>> document_qa( ... image="https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/invoice.png", ... question="What is the invoice number?", ... ) - >>> result[0]["answer"] - '1110212019' + [{'score': 0.425, 'answer': 'us-001', 'start': 16, 'end': 16}] ``` [Learn more about the basics of using a pipeline in the [pipeline tutorial]](../pipeline_tutorial) diff --git a/src/transformers/pipelines/token_classification.py b/src/transformers/pipelines/token_classification.py index 4ff3ee68005e..03242eea4705 100644 --- a/src/transformers/pipelines/token_classification.py +++ b/src/transformers/pipelines/token_classification.py @@ -95,7 +95,8 @@ class TokenClassificationPipeline(Pipeline): >>> token_classifier = pipeline(model="Jean-Baptiste/camembert-ner", aggregation_strategy="simple") >>> sentence = "Je m'appelle jean-baptiste et je vis à montréal" - >>> token_classifier(sentence) + >>> tokens = token_classifier(sentence) + >>> tokens [{'entity_group': 'PER', 'score': 0.9931, 'word': 'jean-baptiste', 'start': 12, 'end': 26}, {'entity_group': 'LOC', 'score': 0.998, 'word': 'montréal', 'start': 38, 'end': 47}] >>> token = tokens[0] diff --git a/src/transformers/pipelines/zero_shot_classification.py b/src/transformers/pipelines/zero_shot_classification.py index 12653ba6e039..99c707990a61 100644 --- a/src/transformers/pipelines/zero_shot_classification.py +++ b/src/transformers/pipelines/zero_shot_classification.py @@ -61,7 +61,7 @@ class ZeroShotClassificationPipeline(ChunkPipeline): >>> from transformers import pipeline >>> oracle = pipeline(model="facebook/bart-large-mnli") - >>> answers = oracle( + >>> oracle( ... "I have a problem with my iphone that needs to be resolved asap!!", ... candidate_labels=["urgent", "not urgent", "phone", "tablet", "computer"], ... )