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app.py
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#Python版本的transformers pipeline API
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#https://huggingface.co/docs/transformers/main_classes/pipelines
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#Java版本的transformers pipeline API
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#https://huggingface.co/docs/transformers.js/pipelines#available-tasks
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#Python版本示例:https://huggingface.co/docs/transformers/main_classes/pipelines
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from transformers import pipeline, AutoModelForTokenClassification, AutoTokenizer
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# Sentiment analysis pipeline
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analyzer = pipeline("sentiment-analysis")
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#sentiment-analysis的default model是distilbert-base-uncased-finetuned-sst-2-english
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#https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english?text=I+like+you.+I+love+you
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#https://huggingface.co/blog/sentiment-analysis-python
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# Question answering pipeline, specifying the checkpoint identifier
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oracle = pipeline(
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"question-answering", model="distilbert-base-cased-distilled-squad", tokenizer="bert-base-cased"
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)
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# Named entity recognition pipeline, passing in a specific model and tokenizer
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model = AutoModelForTokenClassification.from_pretrained("dbmdz/bert-large-cased-finetuned-conll03-english")
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tokenizer = AutoTokenizer.from_pretrained("bert-base-cased")
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recognizer = pipeline("ner", model=model, tokenizer=tokenizer)
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