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fairseq2 Documentation
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fairseq2 Documentation

Getting Started

  • Installation
    • Installing from Source
  • Quick Start

Basics

  • Overview
  • Design Philosophy
  • CLI
  • Assets
  • Data Pipeline
  • Checkpoint Management
  • Recipes
  • Runtime Extensions
  • Gang
  • Trainer

Tutorials

  • End-to-End Fine-Tuning
  • Monitor Your Experiments
  • Working with Presets
  • Efficient Benchmarking
  • Debugging with PuDB
  • Add Your Own Model

FAQ

  • Contributing to fairseq2

Reference

  • API Reference
    • fairseq2
    • fairseq2.gang
    • fairseq2.data
      • fairseq2.data.text
        • Text Tokenizers
      • fairseq2.data.data_pipeline
    • fairseq2.datasets
      • Dataset Loaders
    • fairseq2.nn
      • Position Encoders
    • fairseq2.recipes
      • fairseq2.recipes.lm
        • fairseq2.recipes.lm.instruction_finetune
      • fairseq2.recipes.llama
        • Convert Checkpoints
      • fairseq2.recipes.wav2vec2
        • fairseq2.recipes.wav2vec2.train
      • fairseq2.recipes.cli
      • fairseq2.recipes.trainer
    • fairseq2.assets
  • Bibliography
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fairseq2.recipesΒΆ

This module contains various recipes for training, evaluation, and inference of different model architectures.

  • fairseq2.recipes.lm
  • fairseq2.recipes.llama
  • fairseq2.recipes.wav2vec2
  • fairseq2.recipes.cli
  • fairseq2.recipes.trainer
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fairseq2.recipes.lm
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Position Encoders
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