This repository highlights the LLMs reasoning capabilities of ✨ Mistral / LLaMA-3 / Phi-3 / Gemma / Flan-T5 / GPT-4o ✨ in Targeted Sentiment Analysis in Russian / Translated to English mass-media 📊

Learn linear quantization techniques using the Quanto library and downcasting methods with the Transformers library to compress and optimize generative AI models effectively.

A study to benchmark whisper based ASRs in Malayalam

Extensible implementation of a Language Model (LLM) training framework in Scala.

Language Modelling (text generation, spell correction) and Sentiment Analysis / POS Tagging with MLP, RNN, CNN and BERT models and LLM prompting

"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.

PhoBERT: Pre-trained language models for Vietnamese (EMNLP-2020 Findings)

Re-implementation of the method proposed in the paper "Style Aligned Image Generation via Shared Attention" in PyTorch.

An ASR (Automatic Speech Recognition) adversarial attack repository.

BETO - Spanish version of the BERT model

Training a BERT model from scratch.

This Python application leverages the Flask framework to create an interactive chatbot powered by the Microsoft DialoGPT model. The chatbot engages users in meaningful conversations, providing human-like responses to their input.

Contextual Emotion Detection in Text (DoubleDistilBert Model)

GUI based YouTube Transcriptor developed using Flask

ML (Machine Learning)/NLP project for extraction of Names, Aadhar ID, PAN numbers. It uses Pytesseract OCR for extracting text from images, and uses Hugging Face NER model for Name extraction and regex library for extracting PAN and Aadhaar ID numbers.

How to fine-tune transformer models for text classification using Hugging Face Transformers and Datasets

DIET Classifier mini implementation on pytorch.

AllenNLP integration for Shiba: Japanese CANINE model

Multi-Label Text Classification by fine-tuning BERT and XLNet and deployment using Flask