Popular GitHub Repositories for Ngram Decoding

LightSeq: A High Performance Library for Sequence Processing and Generation

Medusa: Simple Framework for Accelerating LLM Generation with Multiple Decoding Heads

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

? Build your chatbot within minutes on your favorite device; offer SOTA compression techniques for LLMs; run LLMs efficiently on Intel Platforms?

Large-scale LLM inference engine

Four word embedding models implemented in Python. Supporting arbitrary context features

Connectionist Temporal Classification (CTC) decoding algorithms: best path, beam search, lexicon search, prefix search, and token passing. Implemented in Python.

A Lite Bert For Self-Supervised Learning Language Representations

EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.

Official implementation for the paper "DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models"

DGMs for NLP. A roadmap.

Official code base for MinD-Video

scalable and robust tree-based speculative decoding algorithm

PyTorch implementation of beam search decoding for seq2seq models

Code for "LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding", ACL 2024

Efficient and general syntactical decoding for Large Language Models

Code and Data artifact for NeurIPS 2023 paper - "Monitor-Guided Decoding of Code LMs with Static Analysis of Repository Context". `multispy` is a lsp client library in Python intended to be used to build applications around language servers.

DashInfer is a native LLM inference engine aiming to deliver industry-leading performance atop various hardware architectures, including CUDA, x86 and ARMv9.

[COLM 2024] TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding

[ICLR2025 Spotlight] MagicPIG: LSH Sampling for Efficient LLM Generation