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NeMo Framework

  • Overview
  • Performance
  • Why NeMo Framework?

Quickstart

  • Getting Started
  • Playbooks

NeMo 2.0

  • Overview
  • Quickstart with NeMo-Run
  • Migration Guide
  • Feature Guide
  • Large Language Models
  • Long Context Recipe

Training and Customization

  • SFT and PEFT
  • Continual Learning with Pretrained Checkpoints
  • RAG
  • Optimizing Models with Pruning
  • Optimizing Models with Knowledge Distillation

Models

  • Large Language Models
  • Multimodal Models
  • Embedding Models
  • Speech AI Models

Deploy Models

  • Overview
  • NeMo Large Language Models
  • NeMo Multimodal Models

Library Documentation

  • Overview
  • NeMo
  • NeMo Framework Launcher
  • NeMo Aligner
  • NeMo Curator

Cloud Service Providers

  • Overview

Releases

  • Software Component Versions
  • Changelog
  • Known Issues
NVIDIA NeMo Framework User Guide
  • »
  • NLP Tasks
  •  

Important

NeMo 2.0 is an experimental feature and currently released in the dev container only: nvcr.io/nvidia/nemo:dev. Please refer to NeMo 2.0 overview for information on getting started.

NLP Tasks

NeMo’s NLP collection supports provides the following task-specific models:

  • Punctuation And Capitalization Models
  • SpellMapper (Spellchecking ASR Customization) Model
  • Token Classification (Named Entity Recognition) Model
  • Joint Intent and Slot Classification
  • Text Classification model
  • BERT
  • Language Modeling
  • Question Answering
  • Dialogue tasks
  • GLUE Benchmark
  • BERT Embedding Models
  • GPT Embedding Models
  • Entity Linking
  • Model NLP
  • Machine Translation Models

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Last updated on Dec 23, 2024.