mudler/magpie-tts.cpp-gguf
text-to-speech model by mudler
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Model card & documentation
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Brought to you by the LocalAI team, the folks behind LocalAI, the open-source AI engine that runs any model (LLMs, vision, voice, image, video) on any hardware, no GPU required. Self-contained GGUF builds of NVIDIA's Magpie TTS Multilingual 357M for magpie-tts.cpp, a from-scratch C++17/ggml inference engine. Each file bundles the TTS model, the NanoCodec decoder, the tokenizer and the G2P dictionaries: one file, no Python, PyTorch, NeMo, or CUDA toolkit at inference. 5 voices (Aria, Jason, John, Leo, Sofia), 22.05 kHz mono, 9+ languages (en, es, de, fr, it, pt-BR, hi, vi, ko, ar variants; zh/ja not yet supported by the C++ tokenizer). Quantization is selective (only matmul weights; codec and embeddings stay f32). Full drift numbers and methodology: docs/quantization.md. About…
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Model overview
mudler/magpie-tts.cpp-gguf is a text-to-speech model repository published by mudler on Hugging Face. A library was not reported.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-to-speech
- Library
- Not reported
- Recent downloads (30 days)
- 11,962
- Cumulative likes
- 1
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- other
- Access
- Not gated by Hugging Face
- Created
- 2026-07-24T19:58:05.000Z
- Last modified
- 2026-07-24T20:48:15.000Z
Compatibility and lineage
Reported languages: en, es, de, fr, it, pt, hi, vi, ko, ar
Reported base models: nvidia/magpie_tts_multilingual_357m
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-17T06:35:01.183Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.