deep-learning

BERT finetuned on NER downstream tasks

Programmable automated machine learning - proof of concept

Code Repository for the IndicXNLI paper.

A complete roadmap to become an AI/LLM Engineer in 2026. Free & paid courses, 5 portfolio projects, interview prep, and resources. For software engineers with Python & ML basics who want to break into AI. Covers Transformers, RAG, fine-tuning, agents, LangChain, MLOps, and deployment.

NLP model that determines whether a plot is anime enough

SAM + CLIP + DIFFUSION for image to edit objects in images using plain text

A repository of curated use cases, articles, blogs, videos on how companies are using Artificial Intelligence and Machine Learning.

Torch code for Visual Question Generation

Python script to fine tune Open source Video Vision Transformer (ViVit) using HuggingFace Trainer Library

HypeLoRA: Hypernetwork-Generated LoRA Adapters for Calibrated Language Model Fine-Tuning

I implement a deep learning network to classify COVID-19 Tweets into 5 categories and 3 categories using DistilBERT (a lighter version of BERT) as an embedding layer along with an LSTM and Dense Layer. I Achieve 65% accuracy with 5 categories and 80% accuracy on 3 categories.

A game where you need to guess whether a tweet comes from a human, or from a neural network language model trained on a category of tweets.

Serving large language model with transformers

Code for paper "Modality Plug-and-Play: Elastic Modality Adaptation in Multimodal LLMs for Embodied AI"

Engage in a semantic segmentation challenge for land cover description using multimodal remote sensing earth observation data, delving into real-world scenarios with a dataset comprising 70,000+ aerial imagery patches and 50,000 Sentinel-2 satellite acquisitions.

FeelingBlue: A Corpus for Understanding the Emotional Connotation of Color in Context, accepted at TACL 2022, presented at ACL 2023

预训练模型知识量度量竞赛 Baseline F1 0.35 BERTForMaskedLM

🧠 Multimodal Retrieval-Augmented Generation that "weaves" together text and images seamlessly. 🪡

Comprehensive LLMs repo, where I cover both theoretical and practical aspects of LLMs.

Unsupervised specificity-guided optimization of Image Captioning models to encourage meaningful diversity in the generated captions. Code for the paper Generating Diverse and Meaningful Captions: Unsupervised Specificity Optimization for Image Captioning (Lindh et al., 2018).