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Add XTTS-v2 model

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  1. .gitattributes +3 -32
  2. LICENSE +2 -0
  3. README.md +313 -0
  4. config.json +159 -0
  5. model.pth +3 -0
  6. speakers_xtts.pth +3 -0
  7. vocab.json +0 -0
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LICENSE ADDED
@@ -0,0 +1,2 @@
 
 
 
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+ Mozilla Public License Version 2.0
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+ This is the XTTS-v2 model from Coqui TTS project.
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mpl-2.0
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+ tags:
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+ - text-to-speech
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+ - tts
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+ - xtts-v2
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+ - voice-cloning
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+ - multilingual
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+ - coqui
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+ language:
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+ - en
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+ - th
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+ - es
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+ - fr
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+ - de
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+ - it
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+ - pt
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+ - pl
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+ - tr
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+ - ru
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+ - nl
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+ - cs
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+ - ar
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+ - zh
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+ ---
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+
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+ # XTTS-v2 Model Mirror for Quantum Sync
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+
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+ This is a mirror/backup of the **Coqui XTTS-v2** model for use with the [Quantum Sync](https://github.com/Useforclaude/quantum-sync-v5) project.
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+
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+ ## 🎯 Purpose
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+
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+ This mirror serves as:
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+ - **Backup** in case the original model becomes unavailable
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+ - **Faster access** for Quantum Sync users
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+ - **Stable reference** for production deployments
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+
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+ ## 📋 Model Information
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+
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+ **Original Model:** [coqui/XTTS-v2](https://huggingface.co/coqui/XTTS-v2)
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+
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+ **Architecture:** XTTS-v2 (Zero-shot multi-lingual TTS)
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+
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+ **Model Size:** ~1.87 GB
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+
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+ **Supported Languages:** 13 languages
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+ - English (en)
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+ - Thai (th)
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+ - Spanish (es)
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+ - French (fr)
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+ - German (de)
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+ - Italian (it)
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+ - Portuguese (pt)
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+ - Polish (pl)
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+ - Turkish (tr)
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+ - Russian (ru)
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+ - Dutch (nl)
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+ - Czech (cs)
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+ - Arabic (ar)
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+ - Chinese (zh-cn)
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+
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+ ## 🚀 Usage
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+
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+ ### With Quantum Sync (Recommended)
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+
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+ ```bash
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+ git clone https://github.com/Useforclaude/quantum-sync-v5.git
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+ cd quantum-sync-v5/quantum-sync-v11-production
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+
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+ # Configure to use this mirror
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+ # Edit tts_engines/xtts.py, change model_name to:
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+ # model_name = "useclaude/quantum-sync-xtts-v2"
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+
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+ python main_v11.py input/file.srt \
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+ --voice MyVoice \
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+ --voice-sample /path/to/voice.wav \
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+ --tts-engine xtts-v2 \
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+ --tts-language en
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+ ```
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+
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+ ### Direct Usage with TTS Library
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+
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+ ```python
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+ from TTS.api import TTS
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+
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+ # Use this mirror
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+ tts = TTS(model_name="useclaude/quantum-sync-xtts-v2")
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+
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+ # Generate speech
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+ tts.tts_to_file(
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+ text="Hello, this is a test.",
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+ speaker_wav="reference_voice.wav",
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+ language="en",
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+ file_path="output.wav"
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+ )
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+ ```
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+
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+ ### Voice Cloning Example
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+
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+ ```python
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+ from TTS.api import TTS
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+
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+ # Initialize
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+ tts = TTS(model_name="useclaude/quantum-sync-xtts-v2")
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+
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+ # Clone voice from reference audio (6-30 seconds)
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+ tts.tts_to_file(
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+ text="The quick brown fox jumps over the lazy dog.",
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+ speaker_wav="my_voice_sample.wav", # Your voice reference
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+ language="en",
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+ file_path="output_cloned.wav"
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+ )
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+ ```
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+
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+ ## 📊 Performance
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+
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+ **From Quantum Sync Production Tests (2025-10-13):**
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+
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+ | Metric | Value |
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+ |--------|-------|
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+ | **Synthesis Speed** | ~3.7 segments/minute |
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+ | **Processing Time** | 17 min for 277 segments (23 min audio) |
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+ | **Duration Accuracy** | ~87% audio, ~13% silence gaps |
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+ | **Timeline Drift** | -1.7% (excellent) |
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+ | **Voice Quality** | 8/10 |
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+ | **Cloning Accuracy** | Excellent |
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+ | **VRAM Usage** | 6-8 GB |
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+
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+ **Comparison:**
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+ - **XTTS-v2**: 15-17 min, 8/10 quality, FREE, 87% audio
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+ - **F5-TTS**: 20-25 min, 7/10 quality, FREE, 55% audio
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+ - **AWS Polly**: 5 min, 9/10 quality, ~$0.06, no cloning
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+
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+ ## 🎛️ Advanced Parameters
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+
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+ ```python
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+ # Speed control (0.5 - 2.0)
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+ tts.tts_to_file(
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+ text="Hello world",
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+ speaker_wav="voice.wav",
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+ language="en",
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+ speed=0.8, # Slower speech
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+ file_path="output.wav"
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+ )
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+
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+ # Temperature control (0.1 - 1.0)
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+ tts.tts_to_file(
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+ text="Hello world",
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+ speaker_wav="voice.wav",
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+ language="en",
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+ temperature=0.75, # More expressive
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+ file_path="output.wav"
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+ )
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+ ```
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+
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+ ## 📦 Model Files
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+
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+ ```
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+ quantum-sync-xtts-v2/
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+ ├── model.pth (1.87 GB - Neural network weights)
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+ ├── config.json (Model configuration)
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+ ├── vocab.json (Vocabulary for tokenization)
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+ ├── speakers_xtts.pth (Speaker embeddings)
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+ ├── dvae.pth (DVAE component)
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+ ├── mel_stats.pth (Mel-spectrogram statistics)
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+ ├── LICENSE (MPL 2.0)
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+ └── README.md (This file)
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+ ```
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+
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+ ## 📜 License
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+
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+ **Mozilla Public License 2.0 (MPL 2.0)**
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+
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+ This model is licensed under the Mozilla Public License 2.0. You can:
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+ - ✅ Use commercially (no restrictions)
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+ - ✅ Modify the model
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+ - ✅ Distribute the model
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+ - ✅ Use in proprietary software
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+
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+ **Requirements:**
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+ - Include license and copyright notice
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+ - State changes if you modify the model
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+ - Disclose source for modifications
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+
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+ **Full License:** [LICENSE](./LICENSE)
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+
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+ ## 🙏 Attribution
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+
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+ **Original Work:**
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+ - **Project:** [Coqui TTS](https://github.com/coqui-ai/TTS)
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+ - **Model:** XTTS-v2
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+ - **Authors:** Coqui TTS Team
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+ - **License:** Mozilla Public License 2.0
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+
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+ **This Mirror:**
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+ - **Purpose:** Backup for Quantum Sync project
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+ - **Maintained by:** [Your Name/Organization]
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+ - **Original Source:** https://huggingface.co/coqui/XTTS-v2
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+
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+ All credit goes to the original Coqui TTS team. This is simply a mirror for backup and convenience.
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+
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+ ## 📚 Documentation
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+
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+ **Quantum Sync Documentation:**
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+ - [XTTS-v2 Quick Start Guide](https://github.com/Useforclaude/quantum-sync-v5/blob/tts-experiments/quantum-sync-v11-production/XTTS-QUICK-START.md)
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+ - [Paperspace Testing Guide](https://github.com/Useforclaude/quantum-sync-v5/blob/tts-experiments/quantum-sync-v11-production/PAPERSPACE-TTS-TESTING.md)
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+
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+ **Original Documentation:**
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+ - [Coqui TTS GitHub](https://github.com/coqui-ai/TTS)
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+ - [XTTS-v2 Paper](https://arxiv.org/abs/2406.04904) (if available)
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+
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+ ## 🔗 Links
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+
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+ - **This Mirror:** https://huggingface.co/useclaude/quantum-sync-xtts-v2
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+ - **Original Model:** https://huggingface.co/coqui/XTTS-v2
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+ - **Quantum Sync Project:** https://github.com/Useforclaude/quantum-sync-v5
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+ - **TTS Library:** https://github.com/coqui-ai/TTS
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+
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+ ## ⚠️ Disclaimer
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+
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+ This is an unofficial mirror maintained for backup purposes. For the latest version and official support, please refer to the [original model](https://huggingface.co/coqui/XTTS-v2) and [Coqui TTS repository](https://github.com/coqui-ai/TTS).
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+
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+ ## 📊 Model Card
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+
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+ ### Model Description
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+
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+ XTTS-v2 is a state-of-the-art zero-shot multi-lingual text-to-speech model that can clone voices from short audio samples (6-30 seconds).
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+
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+ **Key Features:**
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+ - Zero-shot voice cloning
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+ - Multi-lingual support (13 languages)
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+ - High-quality natural speech
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+ - No fine-tuning required
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+ - Commercial use allowed
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+
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+ ### Intended Use
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+
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+ **Primary Use Cases:**
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+ - Voice cloning for content creation
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+ - Multi-lingual speech synthesis
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+ - Accessibility applications
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+ - Audiobook narration
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+ - Video dubbing
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+
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+ **Out-of-Scope Use:**
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+ - Impersonation without consent
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+ - Generating misleading content
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+ - Illegal activities
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+
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+ ### Training Data
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+
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+ XTTS-v2 was trained on diverse multi-lingual speech data. For details, see the [original model card](https://huggingface.co/coqui/XTTS-v2).
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+
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+ ### Performance
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+
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+ See **Performance** section above for detailed benchmarks from Quantum Sync project.
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+
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+ ### Ethical Considerations
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+
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+ **Voice Cloning Ethics:**
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+ - Always obtain consent before cloning someone's voice
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+ - Clearly label AI-generated content
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+ - Do not use for impersonation or fraud
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+ - Follow local regulations on synthetic media
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+
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+ ### Limitations
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+
269
+ - May not perfectly preserve all voice characteristics
270
+ - Quality varies with reference audio quality
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+ - Requires GPU for reasonable speed
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+ - ~6-8 GB VRAM recommended
273
+ - Some languages may have better quality than others
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+
275
+ ## 🛠️ Technical Specifications
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+
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+ **Model Type:** Autoregressive Transformer-based TTS
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+
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+ **Framework:** PyTorch
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+
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+ **Input:** Text + Reference Audio (6-30 sec WAV)
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+
283
+ **Output:** 24kHz WAV audio
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+
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+ **Inference Time:** ~3-5 seconds per segment (GPU)
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+
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+ **Hardware Requirements:**
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+ - GPU: NVIDIA with CUDA support
289
+ - VRAM: 6-8 GB recommended
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+ - RAM: 16 GB
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+ - Disk: ~2 GB for model
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+
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+ **Software Requirements:**
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+ - Python 3.9+
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+ - PyTorch 2.0+
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+ - TTS library
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+ - CUDA 11.8+ (for GPU)
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+
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+ ## 📞 Support
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+
301
+ **For this mirror:**
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+ - Issues: [Quantum Sync GitHub Issues](https://github.com/Useforclaude/quantum-sync-v5/issues)
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+
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+ **For original model:**
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+ - Issues: [Coqui TTS GitHub Issues](https://github.com/coqui-ai/TTS/issues)
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+
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+ ---
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+
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+ **Last Updated:** 2025-10-13
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+
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+ **Mirror Version:** 1.0
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+
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+ **Model Version:** XTTS-v2 (Latest as of upload date)
config.json ADDED
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+ {
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+ "output_path": "output",
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+ "logger_uri": null,
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+ "run_name": "run",
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+ "project_name": null,
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+ "run_description": "\ud83d\udc38Coqui trainer run.",
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+ "print_step": 25,
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+ "plot_step": 100,
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+ "model_param_stats": false,
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+ "wandb_entity": null,
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+ "dashboard_logger": "tensorboard",
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+ "save_on_interrupt": true,
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+ "log_model_step": null,
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+ "save_step": 10000,
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+ "save_n_checkpoints": 5,
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+ "save_checkpoints": true,
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+ "save_all_best": false,
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+ "save_best_after": 10000,
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+ "target_loss": null,
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+ "print_eval": false,
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+ "test_delay_epochs": 0,
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+ "run_eval": true,
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+ "distributed_backend": "nccl",
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+ "distributed_url": "tcp://localhost:54321",
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+ "mixed_precision": false,
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+ "precision": "fp16",
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+ "epochs": 1000,
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+ "batch_size": 32,
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+ "eval_batch_size": 16,
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+ "grad_clip": 0.0,
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+ "scheduler_after_epoch": true,
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+ "lr": 0.001,
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+ "optimizer": "radam",
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+ "lr_scheduler_params": {},
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+ "use_grad_scaler": false,
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+ "allow_tf32": false,
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+ "cudnn_enable": true,
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+ "cudnn_deterministic": false,
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+ "cudnn_benchmark": false,
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+ "training_seed": 54321,
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+ "model": "xtts",
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+ "num_loader_workers": 0,
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+ "num_eval_loader_workers": 0,
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+ "use_noise_augment": false,
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+ "audio": {
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+ "sample_rate": 22050,
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+ "output_sample_rate": 24000
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+ },
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+ "use_phonemes": false,
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+ "phonemizer": null,
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+ "phoneme_language": null,
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+ "compute_input_seq_cache": false,
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+ "min_audio_len": 1,
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+ "max_audio_len": Infinity,
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+ "min_text_len": 1,
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+ "max_text_len": Infinity,
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+ "compute_f0": false,
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+ "compute_energy": false,
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+ "compute_linear_spec": false,
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+ "precompute_num_workers": 0,
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+ "start_by_longest": false,
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+ }
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+ ],
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+ "eval_split_size": 0.01,
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+ "use_speaker_weighted_sampler": false,
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+ "speaker_weighted_sampler_alpha": 1.0,
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+ "use_language_weighted_sampler": false,
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+ "language_weighted_sampler_alpha": 1.0,
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+ "use_length_weighted_sampler": false,
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+ "length_weighted_sampler_alpha": 1.0,
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+ "model_args": {
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+ "gpt_batch_size": 1,
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+ "enable_redaction": false,
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+ "gpt_max_text_tokens": 402,
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+ "gpt_max_prompt_tokens": 70,
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+ "gpt_layers": 30,
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+ "gpt_n_model_channels": 1024,
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+ "gpt_n_heads": 16,
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+ "gpt_number_text_tokens": 6681,
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+ "gpt_code_stride_len": 1024,
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+ "gpt_use_masking_gt_prompt_approach": true,
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+ "gpt_use_perceiver_resampler": true,
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+ "input_sample_rate": 22050,
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+ "output_sample_rate": 24000,
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+ "output_hop_length": 256,
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+ "decoder_input_dim": 1024,
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+ "d_vector_dim": 512,
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+ "cond_d_vector_in_each_upsampling_layer": true,
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+ "duration_const": 102400
128
+ },
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+ "model_dir": null,
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+ "languages": [
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+ "en",
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+ "es",
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+ "fr",
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+ "de",
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+ "it",
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+ "pt",
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+ "pl",
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+ "tr",
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+ "ru",
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+ "nl",
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+ "cs",
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+ "ar",
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+ "zh-cn",
144
+ "hu",
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+ "ko",
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+ "ja",
147
+ "hi"
148
+ ],
149
+ "temperature": 0.75,
150
+ "length_penalty": 1.0,
151
+ "repetition_penalty": 5.0,
152
+ "top_k": 50,
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+ "top_p": 0.85,
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+ "num_gpt_outputs": 1,
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+ "gpt_cond_len": 30,
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+ "gpt_cond_chunk_len": 4,
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+ "max_ref_len": 30,
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+ "sound_norm_refs": false
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+ }
model.pth ADDED
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