Popular GitHub Repositories for Input Output

A game theoretic approach to explain the output of any machine learning model.

The AI framework that adds the engineering to prompt engineering (Python/TS/Ruby/Java/C#/Rust/Go compatible)

Prompt Engineering | Prompt Versioning | Use GPT or other prompt based models to get structured output. Join our discord for Prompt-Engineering, LLMs and other latest research

Python telegram bot, which utilizes the OpenAI API for implementing GPT-4 and speech-to-text functionality. The bot handles text and voice input from users, transcribes voice input to text, and generates responses using GPT-4

Data & AI Notebook templates catalog organized by tools, following the IMO (input, model, output) framework for easy usage and discovery..

Enhance Tesseract OCR output for scanned PDFs by applying Large Language Model (LLM) corrections.

Provide an input CSV and a target field to predict, generate a model + code to run it.

Run AI models locally on your machine with node.js bindings for llama.cpp. Enforce a JSON schema on the model output on the generation level

solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning

TrustRAG：The RAG Framework within Reliable input,Trusted output

3D mesh stylization driven by a text input in PyTorch

Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)

Hypernetworks that adapt LLMs for specific benchmark tasks using only textual task description as the input

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

Emacs as your personal AI assistant. Use LLMs such as ChatGPT or LLaMA for text generation or DALL-E and Stable Diffusion for image generation. Also supports speech input / output.

Official repository accompanying a CVPR 2022 paper EMOCA: Emotion Driven Monocular Face Capture And Animation. EMOCA takes a single image of a face as input and produces a 3D reconstruction. EMOCA sets the new standard on reconstructing highly emotional images in-the-wild

LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.

A CLI text-to-speech tool using the Kokoro model, supporting multiple languages, voices (with blending), and various input formats including EPUB books and PDF documents.

convert mmdetection model to tensorrt, support fp16, int8, batch input, dynamic shape etc.

The llama-cpp-agent framework is a tool designed for easy interaction with Large Language Models (LLMs). Allowing users to chat with LLM models, execute structured function calls and get structured output. Works also with models not fine-tuned to JSON output and function calls.