Create README

README.md

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+---
+license: mit
+tags:
+- audio
+- speech
+- phonology
+- wav2vec2
+- multilingual
+- pytorch-lightning
+language:
+- en
+- es
+- de
+- cs
+pipeline_tag: audio-classification
+---
+
+# PhonoQ 2.0 – Multilingual
+
+This repository hosts the **multilingual checkpoint** for **PhonoQ 2.0**, a modernized successor to the original PhonoQ system:
+https://github.com/TAriasVergara/PhonoQ
+
+PhonoQ 2.0 outputs **framewise probability distributions** over phonological heads from raw speech audio, built on a self-supervised speech encoder (e.g., wav2vec 2.0 / HuBERT).
+
+## What this model outputs
+
+Given an input audio file, the model produces **framewise head probabilities** for:
+
+- **Manner** (9 classes)
+- **Vowel height** (3 classes)
+- **Vowel backness** (3 classes)
+- **Place of articulation** (5 classes)
+- **Voicing** (2 classes)
+
+Outputs are aligned to the encoder frame rate and returned as probabilities (not hard labels).
+
+## How to use
+
+This checkpoint is intended to be used with the PhonoQ 2.0 inference code:
+https://github.com/abnerLing/PhonoQ-2.0
+
+### 1) Install PhonoQ 2.0 (from GitHub)
+
+Follow the installation instructions in the GitHub repository (PyTorch is required).
+
+### 2) Download this checkpoint
+
+```bash
+wget https://huggingface.co/abnerh/phonoq-2.0-multilingual/resolve/main/best.ckpt