We have hosted the application nemo curator in order to run this application in our online workstations with Wine or directly.


Quick description about nemo curator:

NeMo Curator is a Python library specifically designed for fast and scalable dataset preparation and curation for large language model (LLM) use-cases such as foundation model pretraining, domain-adaptive pretraining (DAPT), supervised fine-tuning (SFT) and paramter-efficient fine-tuning (PEFT). It greatly accelerates data curation by leveraging GPUs with Dask and RAPIDS, resulting in significant time savings. The library provides a customizable and modular interface, simplifying pipeline expansion and accelerating model convergence through the preparation of high-quality tokens. At the core of the NeMo Curator is the DocumentDataset which serves as the the main dataset class. It acts as a straightforward wrapper around a Dask DataFrame. The Python library offers easy-to-use methods for expanding the functionality of your curation pipeline while eliminating scalability concerns.

Features:
  • Data download and text extraction
  • Language identification and separation with fastText and pycld2
  • Text reformatting and cleaning to fix unicode decoding errors via ftfy
  • Document-level deduplication
  • Multilingual heuristic-based filtering
  • Distributed data classification


Programming Language: Python.
Categories:
Large Language Models (LLM)

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