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Welcome to theUrduText Summarization repository powered by m-BART! This project is based on a multilingual variant of the BART model, designed to generate concise and coherent summaries forUrdutext. It uses a finetuned m-BART model and offers a Flask-based web application as a simple GUI for interaction.
Validation Rationale:
The content clearly references Urdu AI development, specifically text summarization using a multilingual model (m-BART), which falls under Urdu NLP research.
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AnAI-powered conversational agent designed to understand and respond inUrdulanguage. Built using natural language processing (NLP) techniques, this chatbot can handle basic conversations.
Validation Rationale:
The content clearly describes an Urdu AI-powered conversational agent using NLP techniques, directly addressing Urdu AI development.
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Collection ofUrdudatasets for POS, NER, Sentiment, Summarization and NLP tasks. - mirfan899/Urdu
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Matched Urdu AI research or model-related signals.
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GitHub
UrduPoetry Generator A Streamlit application that generates beautifulUrdupoetry using a Transformer-based model. This project leverages advanced natural language processing techniques to create coherent and aesthetically pleasing verses inUrdu, offering various text generation methods to enhance creativity and customization.
Validation Rationale:
The post specifically discusses an application using a Transformer-based Urdu language model to generate poetry, directly addressing AI development in Urdu.
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this is my firstAIproject . Contribute to bushra387/Urdu-AI-Assistantdevelopmentby creating an account on GitHub.
Validation Rationale:
The content clearly indicates development of an AI assistant in Urdu, aligning with the specified categories.
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Dec 15, 2024🚀 Feature Description I am working on a project and i need your model but inUrduLanguage Solution Addition ofUrduLanguage prefered trained on conversational Data Alternative Solutions Additiona...
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The content specifically discusses adding a model in Urdu, which is clearly related to Urdu AI development.
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Language Enthusiasts: Discover the impact ofAIon preserving and empowering linguistic diversity. By fine-tuning DistilBERT forUrdusentiment analysis, this project not only advances machine learning but also contributes to a more inclusive and multilingualAIlandscape.
Validation Rationale:
The snippet discusses using a Finetuned DistilBERT model for Urdu sentiment analysis, directly related to Urdu AI development.
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💠Ever imaginedAIcomposing soulfulUrdupoetry just for you? With this deep-learning-based poetry generator, you can provide a single starting line, andAIwill weave beautiful verses that feel truly poetic. 🌿 Built with LSTM neural networks and powered by Streamlit, this interactive web app makes it effortless to create and exploreAI-craftedUrdupoetry!
Validation Rationale:
The content clearly describes a project focused on developing an AI-based Urdu poetry generator, which directly relates to Urdu AI development.
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Machine Learning Book inUrduAuthors: Sana Rasheed & Zeeshan-ul-hassan Usmani Dear Readers, Thank you very much for reading our book. I hope, it will give you a head start to Machine Leanring domain and you will learn different techniques of Supervise Learning, Unsupervise Learn, Semi-Supervise Learning, Recommendation System.
Validation Rationale:
The content refers to a Machine Learning Book inUrdu, which directly pertains to Urdu AI development.
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This is an advancedUrduAIAssistant. Contribute to Artificial53intelligence/urdu-ai-assistant-developmentby creating an account on GitHub.
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The content is specifically about Urdu AI development, focusing on an advanced Urdu AI assistant and related tools.
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The project uses the UMC005 English-UrduParallel Corpus for training and evaluation. The models are based on the Transformer architecture as described in the paper "Attention is All You Need" and the LSTM-based sequence-to-sequence model.
Validation Rationale:
Matched Urdu AI research or model-related signals.
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GitHub
Develop an LSTM-basedUrdunext word prediction model. Collect and preprocessUrdutext data, train the model, and deploy it as a web app or API. Open-source for community contributions andadvancementsinUrduNLP. This project aims to develop a next word prediction model for theUrdulanguage using Long Short-Term Memory (LSTM) neural networks. Next word prediction is a key task in natural ...
Validation Rationale:
The content specifically discusses developing a next word prediction model for Urdu language using LSTM neural networks, which falls under Urdu AI development.
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