v0.1.0 — initial release

MLX-native port of Supertone's Supertonic 3 multilingual TTS. Runs the
full flow-matching + classifier-free-guidance pipeline at ~x100 realtime
on Apple Silicon, with audio cosine 1.0 vs the cached MLX path and
cosine 0.98 vs the upstream ONNX Runtime reference.

Weights are hosted at https://huggingface.co/ambassadia/supertonic-3-mlx
and auto-downloaded on first use; this repository ships the port code,
the model card, audio samples, and a zero-config setup_and_test.sh.

Install:
    pip install git+https://gitea.tavportal.com/olivier/supertonic-3-mlx.git

Quick test:
    git clone https://gitea.tavportal.com/olivier/supertonic-3-mlx.git
    cd supertonic-3-mlx && ./setup_and_test.sh

Licenses (dual): model weights = BigScience Open RAIL-M (Section 4
propagation), port code = Apache-2.0. See LICENSE, LICENSE-CODE, NOTICE.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

NOTICE

@@ -0,0 +1,39 @@
+supertonic-3-mlx
+================
+
+This release is a derivative of the upstream Supertone Supertonic 3
+text-to-speech model and consists of two artefact classes governed by
+two different licenses:
+
+  1. The model weights (under ./weights/*.safetensors) are released under
+     the BigScience Open RAIL-M License. The full text is in ./LICENSE and
+     was copied verbatim from
+     https://huggingface.co/Supertone/supertonic-3/blob/main/LICENSE
+     The Attachment A use restrictions (Section 5 + Attachment A clauses
+     (a)–(m)) apply to all downstream use of the model and of any output
+     generated by the model.
+
+  2. The MLX port code (under ./src/supertonic_3_mlx/) is released under
+     the Apache License, Version 2.0. The full text is in ./LICENSE-CODE.
+
+Attribution and modifications statement (BigScience Open RAIL-M Section 4.c):
+
+  Copyright (c) 2026 Supertone Inc.  — original model weights and reference
+    Python/ONNX implementation. Distributed at
+    https://huggingface.co/Supertone/supertonic-3
+  Copyright (c) 2026 Olivier Dupont  — MLX-native port code, weight format
+    conversion (ONNX → safetensors via the 3-stage extractor in
+    ``src/supertonic_3_mlx/pipeline.py:_convert_onnx``), and pipeline
+    optimisations (``mx.compile`` of the CFG Euler loop, cross-attention
+    K/V cache shared across the 5 Euler steps). Distributed at
+    https://huggingface.co/ambassadia/supertonic-3-mlx
+
+The MLX port does not modify the model's learned parameters in any
+semantic sense — the only weight-level transformation is a tensor-shape
+re-layout to match the MLX memory model (e.g. depthwise Conv1d
+``(C, 1, K)`` → ``(C, K, 1)``). Bit-identical audio output to the
+upstream ONNX Runtime reference is preserved up to FP32 accumulation
+noise (cosine ≥ 0.98 on the full pipeline, cosine = 1.00 on the vocoder).
+
+No use of the Supertone trademarks, logos, or trade dress is asserted or
+permitted by this release (BigScience Open RAIL-M Section 8).