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pretrained_path layout, and
each user otherwise has to clone three repos and stitch them together by
hand. This mirror does the stitching once: each checkpoints/<variant>/
subfolder is self-contained — drop it in as pretrained_path and
HeartMuLaGenPipeline.from_pretrained(...) Just Works.AEmotionStudio/heartmula-models/
├── README.md ← this file
├── LICENSE ← Apache-2.0
└── checkpoints/
├── heartmula-3b-happy-new-year/ ← recommended mula
│ ├── HeartMuLa-oss-3B/
│ │ ├── config.json
│ │ ├── model-00001-of-00004.safetensors
│ │ ├── ...
│ │ └── model.safetensors.index.json
│ ├── tokenizer.json
│ ├── gen_config.json
│ ├── README.md ← upstream mula card
│ └── LICENSE
├── heartmula-3b-rl/ ← RL-refined mula
├── heartmula-3b-base/ ← original mula
├── heartmula-3b-happy-new-year-bf16/ ← pre-converted bf16
├── heartmula-3b-rl-bf16/ ← pre-converted bf16
├── heartmula-3b-base-bf16/ ← pre-converted bf16
└── heartcodec-20260123/ ← codec
├── HeartCodec-oss/
│ ├── config.json
│ ├── model-00001-of-00002.safetensors
│ ├── model-00002-of-00002.safetensors
│ └── model.safetensors.index.json
├── README.md
└── LICENSE| Subfolder | Source | Size | Description |
|---|---|---|---|
heartmula-3b-happy-new-year/ | HeartMuLa/HeartMuLa-oss-3B-happy-new-year | ~15.8 GB | Recommended mula (fp32). Best lyrics controllability + overall quality. |
heartmula-3b-rl/ | HeartMuLa/HeartMuLa-RL-oss-3B-20260123 | ~15.8 GB | RL-refined mula (fp32). Stronger style/tag adherence. |
heartmula-3b-base/ | HeartMuLa/HeartMuLa-oss-3B | ~15.8 GB | Original mula release (fp32). Kept for reproducibility against the paper. |
heartmula-3b-happy-new-year-bf16/ | (re-cast from fp32) | ~8 GB | Pre-converted bf16 of the recommended mula. Same runtime quality as the fp32 mirror — heartlib already loads at bf16 dtype either way. Half the download. |
heartmula-3b-rl-bf16/ | (re-cast from fp32) | ~8 GB | Pre-converted bf16 of the RL mula. |
heartmula-3b-base-bf16/ | (re-cast from fp32) | ~8 GB | Pre-converted bf16 of the base mula. |
heartcodec-20260123/ | HeartMuLa/HeartCodec-oss-20260123 | ~6.7 GB | Codec (fp32). Pairs with any mula variant. Heartlib explicitly warns against lower-precision codec output. |
tokenizer.json (9 MB) + gen_config.json (~100 B) come from
HeartMuLa/HeartMuLaGen
and are duplicated into every mula variant subfolder so each is
self-contained — codec subfolders don't need them.pretrained_path:1hf download \
2 --repo-id AEmotionStudio/heartmula-models \
3 --include "checkpoints/heartmula-3b-happy-new-year/**" \
4 --local-dir ./ckpt-mula
5
6hf download \
7 --repo-id AEmotionStudio/heartmula-models \
8 --include "checkpoints/heartcodec-20260123/**" \
9 --local-dir ./ckpt-codec
10
11# Then merge the two into one pretrained_path before calling
12# HeartMuLaGenPipeline.from_pretrained — see heartlib README.pretrained_path
automatically and routes it to heartlib.LICENSE at the repo root + each variant's LICENSE for the full text.1@misc{yang2026heartmulafamilyopensourced,
2 title={HeartMuLa: A Family of Open Sourced Music Foundation Models},
3 author={Dongchao Yang and others},
4 year={2026},
5 eprint={2601.10547},
6 archivePrefix={arXiv},
7 primaryClass={cs.SD}
8}python backend/scripts/mirror_heartmula_to_aemotion.py.