文字分類

善用 Hugging Face

Jacob H. Marquez

Lead Data Engineer

文字分類：情緒分析

依情緒傾向為文字貼標

情緒分析

應用： 評論分析、社群情緒追蹤

情緒圖示

情緒分析：程式範例

from transformers import pipeline


my_pipeline = pipeline(
    "text-classification",
    model="distilbert-base-uncased-finetuned-sst-2-english"
)

print(my_pipeline("Wi-Fi is slower than a snail today!"))

[{'label': 'NEGATIVE', 'score': 0.99}]

文字分類：文法正確性

文法檢查

評估文字文法是否正確

文法正確範例

應用： 文法檢查、語言學習工具

文法正確性：程式範例

from transformers import pipeline


# Create a pipeline for grammar checking
grammar_checker = pipeline(
    task="text-classification",
    model="abdulmatinomotoso/English_Grammar_Checker"
)

# Check grammar of the input text
print(grammar_checker("He eat pizza every day."))

[{'label': 'LABEL_0', 'score': 0.99}]

文字分類：QNLI

檢查前提是否回答了問題
應用： 問答系統、事實查核

QNLI 範例

QNLI：程式範例

from transformers import pipeline


classifier = pipeline(
    task="text-classification",
    model="cross-encoder/qnli-electra-base"
)


classifier("Where is Seattle located?, Seattle is located in Washington state.")

[{'label': 'LABEL_0', 'score': 0.997}]

文字分類：動態類別指派

依內容動態指派類別

類別指派範例

應用： 內容審核、推薦系統

類別指派

動態類別指派：程式範例

classifier = pipeline(
  task="zero-shot-classification", 
  model="facebook/bart-large-mnli")


text = "Hey, DataCamp; we would like to feature your courses in our newsletter!"
categories = ["marketing", "sales", "support"]


output = classifier(text, categories)


print(f"Top Label: {output['labels'][0]} with score: {output['scores'][0]}")

Top Label: support with score: 0.8183

文字分類的挑戰

一起來練習吧！

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