bert

This project focuses on fine-tuning a BERT model for question answering using a limited dataset for illustration purposes.

【2024年版】BERTによるテキスト分類

DrFAQ is a plug-and-play question answering NLP chatbot that can be generally applied to any organisation's text corpora.

Fine-tuning an LLM using a Generic Workflow and Best Practices with PyTorch

BERT Fine-tuning for Aspect Based Sentiment Analysis

Train transformer-based models.

Rental app with in-depth data analysis, interactive data visualization, predictive analytics, and chatbot using Dash. Selected as Plotly-Dash’s Top GenAI Project

AI assistant for Dota 2 with real-time game analysis via GSI and advice from LLM

Detecting Fake News using AI

Plan and train German transformer models.

The Hugging Face API wrapper for Delphi leverages cutting-edge models to deliver powerful features, including object detection, music generation, text classification, sentiment analysis, image segmentation, speech-to-text transcription, and text generation.

Trained Neural Networks (LSTM, HybridCNN/LSTM, PyramidCNN, Transformers, etc.) & comparison for the task of Hate Speech Detection on the OLID Dataset (Tweets).

The traditional machine learning models give a lot of pain when we do not have sufficient labeled data for the specific task or domain we care about to train a reliable model. Transfer learning allows us to deal with these scenarios by leveraging the already existing labeled data of some related task or domain. We try to store this knowledge gained in solving the source task in the source domain and apply it to our problem of interest. In this work, I have utilized Transfer Learning utilizing BertForSequenceClassification model. Also tried RobertaForSequenceClassification and XLNetForSequenceClassification models for Fine-Tuning the Model.

📘 Taiwan-LLM Tutor: Large Language Models for Taiwanese Secondary Education

A Persian Image Captioning model based on Vision Encoder Decoder Models of the transformers🤗.

🚀 Unified NLP Pipelines for Language Models

Comparing state of the art models for text summary generation

Question Answering model based on DistilBERT, trained and evaluated on the SQUAD dataset

indoBERT Base-Uncased fine-tuned on Translated Squad v2.0

My own playground for PLP (Programming Language Processing) using DeepLearning techniques