prabhakars

prabhakar srinivasan's starred repositories

Devika is an Agentic AI Software Engineer that can understand high-level human instructions, break them down into steps, research relevant information, and write code to achieve the given objective. Devika aims to be a competitive open-source alternative to Devin by Cognition AI.

Language:PythonMIT1801100

nider

Python package to add text to images, textures and different backgrounds

Language:PythonMIT14900

RealtimeSTT

A robust, efficient, low-latency speech-to-text library with advanced voice activity detection, wake word activation and instant transcription.

Language:PythonMIT134200

lightfm

A Python implementation of LightFM, a hybrid recommendation algorithm.

Language:PythonApache-2.0468100

medAlpaca

LLM finetuned for medical question answering

Language:PythonGPL-3.045500

stanford_alpaca

Code and documentation to train Stanford's Alpaca models, and generate the data.

Language:PythonApache-2.02920800

ControlNet

Let us control diffusion models!

Language:PythonApache-2.02923400

llama_index

LlamaIndex is a data framework for your LLM applications

Language:PythonMIT3401900

GraphGPT

Extrapolating knowledge graphs from unstructured text using GPT-3 🕵️‍♂️

Language:JavaScriptMIT429400

llama

Inference code for Llama models

Language:PythonNOASSERTION5472400

CARE-GNN

Code for CIKM 2020 paper Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters

Language:PythonApache-2.023900

PyChatGPT

⚡️ Python client for the unofficial ChatGPT API with auto token regeneration, conversation tracking, proxy support and more.

Language:PythonMIT422400

pyChatGPT

An unofficial Python wrapper for OpenAI's ChatGPT API

Language:PythonGPL-3.0134800

OR_location_routing_problem_study

Facility Location and routing problems: Survey, Models and Algorithm

Language:Jupyter Notebook2500

Awesome-Deep-Graph-Anomaly-Detection

Awesome graph anomaly detection techniques built based on deep learning frameworks. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in anomaly detection, graph representation learning, and graph anomaly detection to join this project as contributors and boost further research in this area.

MIT30900

MIDAS

Anomaly Detection on Dynamic (time-evolving) Graphs in Real-time and Streaming manner. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.

Language:C++Apache-2.075800