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Found 6 papers, 3 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 FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale
The performance of a large language model (LLM) depends heavily on the quality and size of its pretraining dataset.
StarCoder 2 and The Stack v2: The Next Generation
Our large model, StarCoder2- 15B, significantly outperforms other models of comparable size.
Ranked #35 on
Code Generation
on MBPP
Can It Edit? Evaluating the Ability of Large Language Models to Follow Code Editing Instructions
These are tasks in which the model is provided a block of code and an instruction to modify the code.
OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents
Large multimodal models trained on natural documents, which interleave images and text, outperform models trained on image-text pairs on various multimodal benchmarks.
Ranked #14 on
MMR total
on MRR-Benchmark
(using extra training data)
XTREME-S: Evaluating Cross-lingual Speech Representations
Covering 102 languages from 10+ language families, 3 different domains and 4 task families, XTREME-S aims to simplify multilingual speech representation evaluation, as well as catalyze research in "universal" speech representation learning.
