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trasnformers

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Developed a Marathi speech-to-text application using the Hugging Face whisper ASR models. Trained the model with a custom audio dataset and fine-tuned it for optimized performance. Deployed the model on the Hugging Face Model Hub, achieving a WER of 0.74 for the base model.

  • Updated Jan 29, 2024
  • Jupyter Notebook

An AI-powered Document Summarization System built with Streamlit and Python. It features an Extractive Track using statistical heuristics (TF-IDF/Frequency vectors) and an Abstractive Track utilizing deep learning (NLP Transformers) to process and synthesize long text documents efficiently. Created as part of the TEYZIX CORE Internship Program....

  • Updated Jun 19, 2026
  • Python

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