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fastc is a simple and lightweight text classification tool based on large language model embeddings. It focuses on CPU execution and uses efficient models such as deepset/tinyroberta-6l-768d to generate embeddings. Text classification is achieved through cosine similarity classification instead of fine-tuning. It can also run multiple classifiers using the same model without adding additional overhead.
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