Instructions to use sammoran-phd/cara-native-acestep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sammoran-phd/cara-native-acestep with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="sammoran-phd/cara-native-acestep")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sammoran-phd/cara-native-acestep", device_map="auto") - PEFT
How to use sammoran-phd/cara-native-acestep with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
CARA-native ACE-Step
This peer-review release contains the two checkpoint-owned ACE-Step interfaces used after Phase 1:
- Phase 2: a CARA-expanded and fine-tuned 0.6B 5 Hz planner LM.
- Exploratory Phase 3: the joint turbo-DiT LoRA adapter plus hierarchical 98-pool/9-family CARA attribution head.
The Phase 3 adapter does not duplicate the multi-gigabyte base DiT. It reloads against the named public ACE-Step base model, keeping the derivative release small and making the base/adapter boundary explicit.
Contents
phase2/lm/:save_pretrainedLM and tokenizer files plus the SFT report.phase3/adapter/: PEFT LoRA adapter for the turbo-DiT.phase3/cara_attribution_head.pt: checkpoint-owned pool/family head.phase3/phase3_checkpoint_manifest.json: base/adapter/head contract.registry/: the exact CARA registry required by both interfaces.evidence/: authoritative Phase 2 and exploratory Phase 3 reports.source/: an exact source snapshot used to load and evaluate the checkpoints.cara_model_manifest.json: byte sizes and SHA-256 values for release files.
Use the immutable phase2-v1 tag, or its resolved Hub commit hash.
Reload Phase 2
hf download sammoran-phd/cara-native-acestep \
--revision phase2-v1 \
--local-dir cara-native-acestep-release
mkdir cara-native-acestep-source
tar -xzf cara-native-acestep-release/source/cara-native-acestep-source.tar.gz \
-C cara-native-acestep-source
cd cara-native-acestep-source
python - <<'PY'
from pathlib import Path
from scripts.benchmark_cara_native_acestep import initialize_lm
handler = initialize_lm(
Path("../cara-native-acestep-release/phase2/lm").resolve()
)
print(type(handler).__name__)
PY
For Phase 3, load the public ACE-Step turbo-DiT through the included fork, then
pass phase3/ as --phase3_checkpoint_dir; the evaluator loads the PEFT adapter
and cara_attribution_head.pt together. The complete locked commands are in
the cara-native-musicmodels Phase 2/3 job specifications.
Evaluation boundary
The Phase 2 0.6B planner interface remained below its predeclared representation/discriminability ceiling. On the 780-waveform balanced fixed-audio core it scored 1.92% exact top-1, 3.46% top-3, 13.46% family accuracy, and 100% registry-valid output. Those are real results, but they are below-ceiling ablation evidence rather than a passed scientific gate.
On the matched exploratory Phase 3 436-waveform comparison, the joint DiT-LoRA-plus-head checkpoint scored 4.13% exact top-1, 10.78% top-3, 30.50% pool-derived family accuracy, and 32.11% direct family accuracy. The broad-family gain is intervention-specific; exact pool attribution did not improve.
Intended use and limitations
This release is intended for research reproduction and controlled interface auditing. It is not a provenance, source-identification, royalty allocation, or safety system. Results come from one source corpus and one training run per checkpoint. Phase 3 is explicitly exploratory.
License
The ACE-Step code and named public base checkpoints are MIT licensed. Retain the included license and upstream attribution when redistributing this release.
Model tree for sammoran-phd/cara-native-acestep
Base model
ACE-Step/Ace-Step1.5