Safetensors
English
llama
sound language model

Model Details

We have developed and released the family llama3s. This family is natively understanding audio and text input.

We continual pretrain on the expanded vocabulary homebrewltd/llama3.1-s-whispervq-init with 900M tokens from homebrewltd/raw-speech-whispervq-v1 dataset.

Model developers Homebrew Research.

Input Text and sound.

Output Text.

Model Architecture Llama-3.

Language(s): English.

Intended Use

Intended Use Cases This family is primarily intended for research applications. This version aims to further improve the LLM on sound understanding capabilities.

Out-of-scope The use of llama3-s in any manner that violates applicable laws or regulations is strictly prohibited.

Training process

Training Metrics Image: Below is a snapshot of the training loss curve visualized.

train_log

Hardware

GPU Configuration: Cluster of 10x NVIDIA A6000-48GB.

GPU Usage:

  • Continual Training: 30 hours.

Training Arguments

We utilize torchtune library for the latest FSDP2 training code implementation.

Parameter Continual Training
Epoch 1
Global batch size 480
Learning Rate 2e-4
Learning Scheduler Cosine with warmup
Optimizer AdamW fused
Warmup Steps 50
Weight Decay 0.01
Max Sequence Length 512

Citation Information

BibTeX:

@article{Llama3-S: Sound Instruction Language Model 2024,
  title={Llama3-S},
  author={Homebrew Research},
  year=2024,
  month=August},
  url={https://huggingface.co/homebrewltd/llama3.1-s-2024-08-15}

Acknowledgement

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Inference API
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Dataset used to train homebrewltd/llama3-s-base-v0.2