A curated list of awesome self-supervised learning methods in videos

Janus-Series: Unified Multimodal Understanding and Generation Models

Make websites accessible for AI agents

Code for the paper "Language Models are Unsupervised Multitask Learners"

g1: Using Llama-3.1 70b on Groq to create o1-like reasoning chains

Efficient Triton Kernels for LLM Training

DSPy: The framework for programming—not prompting—language models

RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.

The official Python Library for the Groq API

PyTorch native post-training library

Adding guardrails to large language models.

🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming

[T-PAMI] Benchmarking and Improving Bird's Eye View Perception Robustness in Autonomous Driving

Everything we actually know about the Apple Neural Engine (ANE)

SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2…

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

Talk2BEV: Language-Enhanced Bird's Eye View Maps (ICRA'24)

MLX: An array framework for Apple silicon

Code for Multilingual Eval of Generative AI paper published at EMNLP 2023

EmotiVoice 😊: a Multi-Voice and Prompt-Controlled TTS Engine

A machine learning project that listens to my TV and mutes the commercials

An AdBlocker for TV

On the Road with GPT-4V(ision): Explorations of Utilizing Visual-Language Model as Autonomous Driving Agent

A curated list of awesome knowledge-driven autonomous driving (continually updated)

MTEB: Massive Text Embedding Benchmark

Code and Checkpoints for "Generate rather than Retrieve: Large Language Models are Strong Context Generators" in ICLR 2023.

POWERBEV, a novel and elegant vision-based end-to-end framework that only consists of 2D convolutional layers to perform perception and forecasting of multiple objects in BEVs.

[ICLR 2024] Efficient Streaming Language Models with Attention Sinks