Search Results for author:
Found 5 papers, 2 papers with code
FQuAD2.0: French Question Answering and Learning When You Don’t Know
This new dataset, comprising a total of almost 80, 000 questions, makes it possible to train French Question Answering models with the ability of distinguishing unanswerable questions from answerable ones.
CroissantLLM: A Truly Bilingual French-English Language Model
We introduce CroissantLLM, a 1. 3B language model pretrained on a set of 3T English and French tokens, to bring to the research and industrial community a high-performance, fully open-sourced bilingual model that runs swiftly on consumer-grade local hardware.
Revisiting Instruction Fine-tuned Model Evaluation to Guide Industrial Applications
Instruction Fine-Tuning (IFT) is a powerful paradigm that strengthens the zero-shot capabilities of Large Language Models (LLMs), but in doing so induces new evaluation metric requirements.
Improving Next-Application Prediction with Deep Personalized-Attention Neural Network
The second module learns job seeker representations.
FQuAD2.0: French Question Answering and knowing that you know nothing
This new dataset, comprising a total of almost 80, 000 questions, makes it possible to train French Question Answering models with the ability of distinguishing unanswerable questions from answerable ones.
