Create README.md

README.md

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