aufklarer/Qwen3-TTS-12Hz-1.7B-Base-MLX-bf16

🤗 Hugging Face 来源text-to-speechapache-2.01.9B 参数3.9 GBsafetensors✓ 1 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo aufklarer/Qwen3-TTS-12Hz-1.7B-Base-MLX-bf16 ./model-folder
需要做种者 →

Qwen3 TTS 12Hz 1.7B Base — MLX bf16

Full-precision bf16 (non-quantized) MLX conversion of Qwen/Qwen3-TTS-12Hz-1.7B-Base for Apple Silicon inference — the highest-quality 1.7B variant.

Usage

Used by speech-swift Qwen3TTS module:

let model = try await Qwen3TTSModel.fromPretrained(
    modelId: "aufklarer/Qwen3-TTS-12Hz-1.7B-Base-MLX-bf16"
)
let audio = try model.synthesize("Hello, world!")
audio speak "Hello, world!" --model 1.7b -o output.wav

Model Details

  • Architecture: Qwen3-TTS (Talker transformer + Code Predictor + speech tokenizer decoder)
  • Parameters: 1.7B
  • Precision: bf16 / fp16 — no quantization (plain Linear weights)
  • Size: ~3.7 GB
  • Sample rate: 24 kHz
  • Codec rate: 12.5 Hz

Performance

Apple Silicon (M-series), MLX, 1.7B variants:

Precision RTF Peak RAM Notes
8-bit 0.39 2.8 GiB good
bf16 0.48 4.1 GiB best quality

Round-trip WER (synthesize → Qwen3-ASR transcribe → WER), 15 sentences: 7.05 % (TTS + ASR round-trip; 0 synthesis failures).

Variants

Variant Precision Size Model ID
0.6B 8-bit 8-bit ~1.3 GB aufklarer/Qwen3-TTS-12Hz-0.6B-Base-MLX-8bit
1.7B 8-bit 8-bit ~2.8 GB aufklarer/Qwen3-TTS-12Hz-1.7B-Base-MLX-8bit
1.7B bf16 bf16 ~3.7 GB aufklarer/Qwen3-TTS-12Hz-1.7B-Base-MLX-bf16