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README.md

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+---
+license: mit
+language:
+- en
+pipeline_tag: text-to-speech
+library_name: loom-py-rt
+---
+# Matcha-TTS (LJSpeech)
+
+Matcha-TTS's LJSpeech flow-matching TTS checkpoint, exported for loom.cpp. Takes phoneme ids, not text.
+
+This is a [loom.cpp](https://github.com/loom-ai-org/loom.cpp) export: a single self-describing GGUF
+that carries its own graph topologies, tokenizer (if any) and driver script, produced by
+[loom-exporter](https://github.com/loom-ai-org/loom-exporter).
+
+## Original model
+
+Exported from [Matcha-TTS (LJSpeech checkpoint)](https://github.com/shivammehta25/Matcha-TTS). Weights are unmodified; this repo packages the same parameters into
+loom.cpp's GGUF format.
+
+## License
+
+`mit`, inherited from the base model above.
+
+## Language(s)
+
+`en`
+
+## Usage
+
+Run it with [loom-py](https://github.com/loom-ai-org/loom-py) -- `loom-py-rt` on PyPI:
+
+```sh
+pip install loom-py-rt[hub]
+```
+
+```python
+import loom
+
+model = loom.Model.from_pretrained("loom-ai-org/matcha-tts-ljspeech-loom")
+# matcha-tts-ljspeech takes phoneme ids, not text -- see model.driver_source for the exact driver inputs.
+audio = model.infer(tokens=[16, 40, 22, 30, 12, 3], n_steps=4, seed=1234)
+```
+
+`model.driver_source` prints the exact driver script this GGUF embeds, including a header comment
+documenting every argument `model.infer()`/`model.generate()` accepts for this model.
+
+## Files
+
+- `matcha-tts-ljspeech.gguf` -- the model, exported with loom-exporter.

matcha-tts-ljspeech.gguf

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