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