KomeijiForce/CoTAM
Official Implementation of the ACL2024 Findings paper "Controllable Data Augmentation for Few-Shot Text Mining with Chain-of-Thought Attribute Manipulation"
This tool helps AI/ML developers quickly create more training examples for text classification models, especially when you only have a small amount of initial data. It takes your existing text data and an OpenAI API key, then uses a large language model to generate diverse, high-quality synthetic training examples. The output is an expanded dataset that you can use to fine-tune smaller language models, making them more accurate for tasks like sentiment analysis, topic categorization, or intent recognition.
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Use this if you are developing or fine-tuning smaller language models for text classification and need to boost their performance, but have limited real-world training data.
Not ideal if you are looking for a no-code solution, do not have an OpenAI API key, or your primary task is not text classification.
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Python
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Last pushed
May 18, 2024
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Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/KomeijiForce/CoTAM"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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