Successfully established a Seq2Seq with attention model which can perform English to Spanish language translation up to an accuracy of almost 97%.
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Updated
May 6, 2024 - Jupyter Notebook
Successfully established a Seq2Seq with attention model which can perform English to Spanish language translation up to an accuracy of almost 97%.
Summarize, , NSP answer questions in dockerised environment
llm-newsletter-generator transforms a valid RSS feed into a "Newsletter" using AI models via PyTorch and Transformers; this is experimental.
Source codes and materials of Advanced Spelling Error Correction project.
Deployed an interactive web platform for exploring and utilizing language models. Features include real-time text analysis and translation, built with Django for robust performance and scalability
With the use of AI, summarise your movies and bring back the colour in older films.
Successfully developed a fine-tuned BERT transformer model which can accurately classify symptoms to their corresponding diseases upto an accuracy of 89%.
Successfully developed a fine-tuned DistilBERT transformer model which can accurately predict the overall sentiment of a piece of financial news up to an accuracy of nearly 81.5%.
With the use of AI, summarise your movies and bring back the colour in older films.
A Python-based REST API for PDF OCR using AI models with PyTorch and Transformers that runs in a Docker container.
Spam Detector is a Data Science Project built using Pytorch and Hugging Face library. Used BERT model based on Transformer Architecture and got 99.97% accuracy on train set and 98.76% accuracy on test set.
"Open Source Models with Hugging Face" course empowers you with the skills to leverage open-source models from the Hugging Face Hub for various tasks in NLP, audio, image, and multimodal domains.
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