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MiniCPM-2B: An end-side LLM outperforming Llama2-13B.
Public repo for the NeurIPS 2023 paper "Unlimiformer: Long-Range Transformers with Unlimited Length Input"
Accessible large language models via k-bit quantization for PyTorch.
A plug-and-play library for parameter-efficient-tuning (Delta Tuning)
Code and documentation to train Stanford's Alpaca models, and generate the data.
PyTorch + HuggingFace code for RetoMaton: "Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval" (ICML 2022), including an implementation of kNN-LM and kNN-MT
Efficient, Low-Resource, Distributed transformer implementation based on BMTrain
Efficient Training (including pre-training and fine-tuning) for Big Models
Running large language models on a single GPU for throughput-oriented scenarios.
[ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
Scalable training for dense retrieval models.
[EMNLP 2022] Training Language Models with Memory Augmentation https://arxiv.org/abs/2205.12674
Contriever: Unsupervised Dense Information Retrieval with Contrastive Learning
This repository provides details and links to the ACL anthology corpus/collection including .bib, .pdf and grobid extractions of the pdfs
Source code and dataset for EMNLP 2020 paper "MAVEN: A Massive General Domain Event Detection Dataset".
A latent text-to-image diffusion model
Official code and model checkpoints for our EMNLP 2022 paper "RankGen - Improving Text Generation with Large Ranking Models" (https://arxiv.org/abs/2205.09726).
A framework for training and evaluating AI models on a variety of openly available dialogue datasets.
The source code of our COLING'18 paper "Few-Shot Charge Prediction with Discriminative Legal Attributes".
Source code and checkpoints for legal pre-trained language models.
Generative model for code infilling and synthesis
A Collection of BM25 Algorithms in Python