rajarampanigrahi's Projects
aiconfig -- config-driven, source control friendly AI application development
Robust recipes for to align language models with human and AI preferences
A one stop repository for generative AI research updates, interview resources, notebooks and much more!
An awesome & curated list of best LLMOps tools for developers
A curated list of awesome Python frameworks, libraries, software and resources
A fully in-browser privacy solution to make Conversational AI privacy-friendly
A customer segmentation project can be approached in multiple ways. In this repository, we will explore advanced techniques for defining clusters and analyzing the results.
Build in-app AI chatbots š¤, and AI-powered Textareas āØ, into react web apps.
This is a repo with links to everything you'd ever want to learn about data engineering
The Evaluation Framework for LLMs
Sample code and notebooks for Generative AI on Google Cloud
Smoothly Manage Multiple LLMs (OpenAI, Anthropic, Azure) and Image Models (Dall-E, SDXL), Speed Up Responses, and Ensure Non-Stop Reliability.
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A tutorial for setting an SQL code generator with the OpenAI API
This repo consists of examples to use langchain
Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning
Call all LLM APIs using the OpenAI format. Use Bedrock, Azure, OpenAI, Cohere, Anthropic, Ollama, Sagemaker, HuggingFace, Replicate (100+ LLMs)
A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain
Examples and recipes for Llama 2 model
Distribute and run LLMs with a single file.
Course with a roadmap and notebooks to get into Large Language Models (LLMs).
LLM Engineering CrashCourse
LLM Finetuning with peft
LLM Prompting Engineering Simplified Book
This is my repository for storing utility snippets for different LLM clients I use in my projects
Providing enterprise-grade LLM-based development framework, tools, and fine-tuned models.
Machine Learning Engineering Online Book
Minimal and clean examples of machine learning algorithms implementations