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Habibi-TTS MLX

The first MLX conversion of Habibi-TTS โ€” an Arabic dialect text-to-speech model built on the F5-TTS architecture.

Overview

This is the Unified Habibi-TTS model converted to Apple MLX format for use with f5-tts-mlx and f5-tts-swift.

  • Architecture: F5-TTS DiT (dim=1024, depth=22, heads=16, ff_mult=2, conv_layers=4)
  • Parameters: 337M (float32)
  • Model size: ~1.3 GB
  • Vocab: 2,731 characters (includes 93 Arabic characters + diacritics)
  • Sample rate: 24 kHz
  • Source: Unified checkpoint from SWivid/Habibi-TTS (200K steps, EMA weights)

Supported Dialects

The Unified model supports multiple Arabic dialects:

Code Dialect
MSA Modern Standard Arabic (ูุตุญู‰)
EGY Egyptian (ู…ุตุฑูŠ)
SAU Saudi (ุณุนูˆุฏูŠ)
UAE Emirati (ุฅู…ุงุฑุงุชูŠ)
IRQ Iraqi (ุนุฑุงู‚ูŠ)
MAR Moroccan (ู…ุบุฑุจูŠ)
ALG Algerian (ุฌุฒุงุฆุฑูŠ)

Usage with f5-tts-mlx (Python)

from f5_tts_mlx.cfm import F5TTS

# Load directly from this repo
f5tts = F5TTS.from_pretrained("pmax-agency/habibi-tts-mlx")

# Generate Arabic speech
wave, _ = f5tts.sample(
    ref_audio,
    text=["ุฃู‡ู„ุงู‹ ูˆุณู‡ู„ุงู‹ุŒ ูƒูŠู ุญุงู„ูƒ ุงู„ูŠูˆู…ุŸ"],
    duration=duration,
    steps=8,
)

Or via CLI:

pip install f5-tts-mlx
python -m f5_tts_mlx.generate \
  --model pmax-agency/habibi-tts-mlx \
  --text "ุฃู‡ู„ุงู‹ ูˆุณู‡ู„ุงู‹" \
  --output arabic_speech.wav

Conversion Details

Converted from the original PyTorch safetensors checkpoint to MLX-compatible format:

  1. Extracted EMA weights (best quality) from the Unified checkpoint
  2. Stripped ema_model. prefix
  3. Removed training metadata (initted, step)
  4. Weight format is compatible with f5-tts-mlx's built-in convert_weights=True conversion

The model_v1.safetensors file contains weights in PyTorch key format โ€” f5-tts-mlx's from_pretrained handles the final key renaming and conv weight transposition automatically.

Credits

License

This model inherits the license from the original Habibi-TTS repository.

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