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--- |
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license: mit |
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datasets: |
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- sartajbhuvaji/gutenberg |
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language: |
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- en |
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base_model: |
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- openai-community/gpt2 |
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pipeline_tag: text-classification |
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library_name: transformers |
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tags: |
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- text-classification |
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--- |
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```python |
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from transformers import GPT2ForSequenceClassification, GPT2Tokenizer |
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from datasets import load_dataset |
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from transformers import pipeline |
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import pandas as pd |
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# Load the model from Hugging Face |
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model = GPT2ForSequenceClassification.from_pretrained('sartajbhuvaji/gutenberg-gpt2') |
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tokenizer = GPT2Tokenizer.from_pretrained("sartajbhuvaji/gutenberg-gpt2") |
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# Create a text classification pipeline |
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classifier = pipeline("text-classification", model=model, tokenizer=tokenizer) |
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# Test the pipeline |
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result = classifier("This is a great book!") |
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print(result) # [{'label': 'LABEL_7', 'score': 0.8302432298660278}] |
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# Test the pipeline on a document |
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doc_id = 1 |
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doc_text = df.loc[df['DocID'] == doc_id, 'Text'].values[0] |
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result = classifier(doc_text[:1024]) |
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print(result) # [{'label': 'LABEL_4', 'score': 0.6285566091537476}] |
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``` |
