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Found 10 papers, 7 papers with code
SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model
To facilitate future research on LM development as well as applications of small LMs, we release both SmolLM2 as well as all of the datasets we prepared in the course of this project.
The N+ Implementation Details of RLHF with PPO: A Case Study on TL;DR Summarization
This work is the first to openly reproduce the Reinforcement Learning from Human Feedback (RLHF) scaling behaviors reported in OpenAI's seminal TL;DR summarization work.
Zephyr: Direct Distillation of LM Alignment
Starting from a dataset of outputs ranked by a teacher model, we apply distilled direct preference optimization (dDPO) to learn a chat model with significantly improved intent alignment.
Ranked #7 on
Zero-Shot Learning
on MedConceptsQA
AfroDigits: A Community-Driven Spoken Digit Dataset for African Languages
The advancement of speech technologies has been remarkable, yet its integration with African languages remains limited due to the scarcity of African speech corpora.
Evaluate & Evaluation on the Hub: Better Best Practices for Data and Model Measurements
We introduce Evaluate and Evaluation on the Hub --a set of tools to facilitate the evaluation of models and datasets in ML.
Efficient Few-Shot Learning Without Prompts
This simple framework requires no prompts or verbalizers, and achieves high accuracy with orders of magnitude less parameters than existing techniques.
GEMv2: Multilingual NLG Benchmarking in a Single Line of Code
This problem is especially pertinent in natural language generation which requires ever-improving suites of datasets, metrics, and human evaluation to make definitive claims.
RAFT: A Real-World Few-Shot Text Classification Benchmark
Will models soon solve classification tasks that have so far been reserved for human research assistants?
Ranked #2 on
Few-Shot Text Classification
on RAFT
Datasets: A Community Library for Natural Language Processing
The scale, variety, and quantity of publicly-available NLP datasets has grown rapidly as researchers propose new tasks, larger models, and novel benchmarks.
giotto-tda: A Topological Data Analysis Toolkit for Machine Learning and Data Exploration
We introduce giotto-tda, a Python library that integrates high-performance topological data analysis with machine learning via a scikit-learn-compatible API and state-of-the-art C++ implementations.
