Showing 741-760 of 3,069 projects
An easy-to-use PyTorch to TensorRT converter for optimizing AI model inference on NVIDIA Jetson devices.
A model for tracking any point (pixel) on a video using optical-flow and point-tracking techniques.
This repository allows developers to train their own medical language models using the ChatGPT training pipeline.
Edward is a probabilistic programming language in TensorFlow for deep generative models and variational inference.
An open-source framework for prompt-learning, a powerful technique for fine-tuning language models.
A Minecraft AI project that leverages Large Language Models and the Mineflayer framework to create intelligent bots.
JSONExport is a desktop app that exports JSON objects as model classes in your favorite language.
Open-source platform for frontier AI/ML workflows, including diffusion models, LLMs, and more.
A collection of important graph embedding, classification and representation learning papers with implementations for vibe coders.
A web UI for interacting with large language models and multimodal AI systems.
Official implementation of a paper on segmentation models for computer vision tasks.
An OpenAI API client library for Java developers to interact with GPT-3 and other OpenAI models.
A TypeScript-based open-source API that provides a reverse-engineered interface to the Kimi AI large language model, with features like stream output, smart agent dialogue, and document parsing.
A lean and efficient codebase for researching large language models (LLMs).
A PyTorch repository for practicing image classification on the CIFAR-100 dataset using various deep learning models.
DiffSinger is a singing voice synthesis system using a shallow diffusion mechanism, enabling efficient TTS and SVS.
A distributed training framework for language models using Reinforcement Learning via Human Feedback (RLHF)
A small, fast GPT model (124M) for quick prototyping and experimentation with AI-powered coding tools.
A curated list of Large Language Model resources for training, serving, fine-tuning, and building LLM applications.
An MLOps framework for packaging, deploying, monitoring, and managing machine learning models.
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