---
license: cc-by-nc-4.0
base_model:
- m-a-p/YuE2-3B
- m-a-p/YuE2-Vae
pipeline_tag: text-to-audio
tags:
- music-generation
- on-device
- android
- geode
---

# Geode · YuE2-3B for phones

[YuE2-3B](https://huggingface.co/m-a-p/YuE2-3B) and [YuE2-Vae](https://huggingface.co/m-a-p/YuE2-Vae) by
[m-a-p](https://huggingface.co/m-a-p), converted for **Geode**, an Android app that runs models on the phone itself:
the song's score, its singing and its band are made on the device, nothing is sent anywhere.

The app downloads one of these packs from its Music settings:

| Pack | Size | For |
|---|---|---|
| `phone/` | 5.45 GiB | every phone: the processor computes the sound (slow without an NPU matrix unit: start with short songs) |
| `phone-npu/` | 8.08 GiB | Snapdragon 8 Gen 2 and newer: the same, plus the AR's fp16 layers for the NPU (the sound's prompt on HMX) |

## What is inside

- `embed.bin` - the token embeddings (bf16).
- `ar_q8.bin` - the 3B transformer for the generation (the ABC score and the codec tokens): int8 weights, per-row
  scales.
- `nar_f16.bin` - the acoustic stage (flow matching, 32 midpoint steps) in fp16, laid out for the Hexagon NPU's matrix
  unit; the processor reads the same file.
- `ar_f16.bin` (`phone-npu/` only) - the transformer's layers in fp16 for the NPU: the acoustic stage's prompt.
- `vae.bin` - YuE2-Vae's decoder (25 Hz latents to 48 kHz stereo).
- `tokenizer.bin` - the model's tokenizer.
- `geode.json` - the pack's manifest (files, tensors, configuration).

The settings are the reference's: cot "full", 32 midpoint ODE steps, context 24576, CFG per song, mastering to
-12.5 LUFS with at most +4 dB. Measured against the reference's fp32 run, the phone's acoustic latents differ by
1.2e-3 (relative L2) - less than the reference's own bf16 run.

## Licence

The weights are **CC BY-NC 4.0**, as the originals: non-commercial use only, with attribution to the YuE2 authors.
See [LICENSE](LICENSE) and the original models' [third-party notices](THIRD_PARTY_NOTICES.md).

YuE2 by the Multimodal Art Projection team: https://github.com/multimodal-art-projection/YuE