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Model Card for t5_small Summarization Model
Model Details
- Model Name: t5-small
- Model Type: Text Summarization
- Architecture: Transformer-based model
- Number of Parameters: Approximately 60 million
Training Data
- Dataset: CNN/Daily Mail
- Data Source: Hugging Face Datasets
- Training Size: X samples (X는 실제 훈련 데이터 수로 교체)
- Data Characteristics: The dataset consists of news articles and their corresponding summaries.
Training Procedure
- Training Framework: Hugging Face Transformers
- Batch Size: 4
- Learning Rate: 2e-5
- Number of Epochs: 1
- Evaluation Metrics: ROUGE, BLEU
How to Use
- Dependencies:
- Install required libraries:
transformers
,datasets
- Install required libraries:
- Example Usage:
from transformers import pipeline summarizer = pipeline("summarization", model="your_model_path") summary = summarizer("Your input text here.")