CODE and DATA

Data, code and models released by NAVER LABS Europe

ELITR-Bench

A benchmark for the evaluation of long-context LLMs on meeting transcripts.

The meeting data used in this benchmark originally comes from the ELITR dataset. This dataset and experiments are described in the paper and are an output of the EU UTTER project.

Pasero

Lightweight Pytorch framework for training and running text generation models.

Can be used for machine translation, speech translation, language modeling and dialogue supporting a number of popular pre-trained models.

DISCo

DIStributional Control of LLMs

A toolkit for controlling language models and other generative models.

Zero-shot task generalization (models)

Multitask prompted training: models (BLOOM BigScience).

These prompted datasets to benchmark the ability of a model to perform completely unseen tasks specified in natural language.

Zero-shot task generalization (prompts)

Multitask prompted training: prompts (BLOOM BigScience).

These prompted datasets to benchmark the ability of a model to perform completely unseen tasks specified in natural language.

Generative Distribution Control (GDC)

Debiasing large pretrained language models using distributional control.

A general framework for imposing constraints on samples of pretrained language models

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