#
ryantd
Follow
Starred repositories
This is a collection of our research on efficient AI, covering hardware-aware NAS and model compression.
Simple and efficient pytorch-native transformer text generation in <1000 LOC of python.
Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
An Easy-to-use, Scalable and High-performance RLHF Framework (70B+ PPO Full Tuning & Iterative DPO & LoRA & Mixtral)
GPT-Fathom is an open-source and reproducible LLM evaluation suite, benchmarking 10+ leading open-source and closed-source LLMs as well as OpenAI's earlier models on 20+ curated benchmarks under al…
An efficient implementation of a rate limiter for asyncio.
a state-of-the-art-level open visual language model | 多模态预训练模型
Fast inference engine for Transformer models
Puck is a high-performance ANN search engine
Robust recipes to align language models with human and AI preferences
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
Adala: Autonomous DAta (Labeling) Agent framework
🛰️ An approximate nearest-neighbor search library for Python and Java with a focus on ease of use, simplicity, and deployability.
Tutorial for Porting PyTorch Transformer Models to Candle (Rust)
Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.
python library for invisible image watermark (blind image watermark)
AgentTuning: Enabling Generalized Agent Abilities for LLMs
Sparsity-aware deep learning inference runtime for CPUs
LLM training code for Databricks foundation models
TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficie…
We jailbreak GPT-3.5 Turbo’s safety guardrails by fine-tuning it on only 10 adversarially designed examples, at a cost of less than $0.20 via OpenAI’s APIs.
Playing Pokemon Red with Reinforcement Learning
[NeurIPS 2023] LLM-Pruner: On the Structural Pruning of Large Language Models. Support LLaMA, Llama-2, BLOOM, Vicuna, Baichuan, etc.
Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads
