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tokenizer-nlp

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Successfully developed a text classification model to predict whether a given news text is fake or not by fine-tuning a pretrained BERT transformed model imported from Hugging Face.

  • Updated Dec 10, 2024
  • Jupyter Notebook

A from-scratch implementation of a small language model, built part by part, from a text file to a system capable of generation, classification, instruction following, parameter-efficient adaptation, and reasoning-style preference training.

  • Updated Sep 20, 2026
  • Python

Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) that teaches computers to understand, interpret, and generate human language. It bridges the gap between human communication and machine understanding, powering everyday tools like digital assistants, spam filters, and language translation.

  • Updated Jun 16, 2026
  • Jupyter Notebook

Tokenization is a way of separating a piece of text into smaller units called tokens. Here, tokens can be either words, characters, or subwords. Hence, tokenization can be broadly classified into 3 types – word, character, and subword (n-gram characters) tokenization.

  • Updated Jun 30, 2021
  • Jupyter Notebook

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