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Spiritlm

Inference code for the paper "Spirit-LM Interleaved Spoken and Written Language Model".

Install / Use

/learn @facebookresearch/Spiritlm
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

Meta Spirit LM: Interleaved Spoken and Written Language Model

This repository contains the model weights, inference code and evaluation scripts for the Spirit LM paper. You can find more generation samples on our demo page.

Spirit LM Model Overview

<img src="assets/spiritlm_overview.png">

Installation Setup

Conda

conda env create -f env.yml
pip install -e '.[eval]'

Pip

pip install -e '.[eval]'

Dev

(Optionally, use only if you want to run the tests.)

pip install -e '.[dev]'

Checkpoints Setup

See checkpoints/README.md

Quick Start

Speech Tokenization

See spiritlm/speech_tokenizer/README.md

Spirit LM Generation

See spiritlm/model/README.md

Speech-Text Sentiment Preservation benchmark (STSP)

See spiritlm/eval/README.md

Model Card

More details of the model can be found in MODEL_CARD.md.

License

The present code is provided under the FAIR Noncommercial Research License found in LICENSE.

Citation

@misc{nguyen2024spiritlminterleavedspokenwritten,
      title={SpiRit-LM: Interleaved Spoken and Written Language Model},
      author={Tu Anh Nguyen and Benjamin Muller and Bokai Yu and Marta R. Costa-jussa and Maha Elbayad and Sravya Popuri and Paul-Ambroise Duquenne and Robin Algayres and Ruslan Mavlyutov and Itai Gat and Gabriel Synnaeve and Juan Pino and Benoit Sagot and Emmanuel Dupoux},
      year={2024},
      eprint={2402.05755},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2402.05755},
}
View on GitHub
GitHub Stars929
CategoryDevelopment
Updated1d ago
Forks64

Languages

Python

Security Score

80/100

Audited on Apr 5, 2026

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