KEYHAN-A/aava-tts-persian-3b

Aava TTS · 3B Merged

Ready-to-load Persian Orpheus model with the Aava LoRA merged into the base, trained from nearly 2,500 hours of Persian source audio.

آوا یک مدل تبدیل متن فارسی به گفتار است که خروجی ۲۴ کیلوهرتز تولید می‌کند.

Quick start

pip install torch transformers snac soundfile numpy
curl -L https://raw.githubusercontent.com/KEYHAN-A/aava-refinement/main/examples/inference.py -o aava_inference.py
python aava_inference.py --text "سلام، من آوا هستم"

The script auto-selects CUDA, Apple MPS, or CPU and downloads KEYHAN-A/aava-tts-persian-3b on first use.

Model card

Architecture	LlamaForCausalLM + SNAC decoder
Parameters	~3.78B
Precision	bfloat16
Storage	~7.59 GB, two safetensors shards
Context	4,096 tokens
Codec / output	SNAC, mono 24 kHz
Language	Persian (fa)

This model is the inference-oriented counterpart of the Aava LoRA adapter.

Training

Setting	Value
Training records	492,596
Tokenized corpus	~1,905.3 hours
Method	LoRA, rank 128, alpha 256
Epochs / steps	3 / 184,725
Effective batch	8
Learning rate	1.5e-4
Precision	bfloat16
Reported eval loss	4.2045

The ~2,400-hour raw-source total must not be confused with the refined training duration.

Training corpus

The training corpus contains 547,328 multi-source, multi-speaker Persian records under one conditioning label (aava).

The reported eval loss is an internal training metric. Exact transcript duplicates cross the original sequential splits, so the metric is not a clean generalization benchmark.

Intended use and limitations

• Persian TTS research, prototyping, and accessibility experiments.
• Other languages and code-switching are unsupported.
• Long generations can repeat or fail to terminate.
• Output voice identity and similarity have not been formally evaluated.
• No v1.0.0 MOS, memorization, latency, or speaker-similarity benchmark exists.
• Do not use for impersonation, fraud, deceptive media, harassment, or identity abuse.

License

The merged weights are Apache-2.0, following the direct Orpheus/Unsloth base. Orpheus is Apache-2.0 and SNAC is MIT licensed. No upstream endorsement is implied.

Related

• Aava LoRA adapter
• Refinement and inference code

Citation

@misc{aava_tts_merged_2026,
  title   = {Aava TTS: Persian Orpheus 3B Merged Model},
  author  = {{KEYHAN-A}},
  year    = {2026},
  version = {1.0.0},
  url     = {https://huggingface.co/KEYHAN-A/aava-tts-persian-3b}
}