Text-to-Speech
Transformers
Safetensors
MLX
higgs_multimodal_qwen3
text-generation
speech-generation
higgs-audio
qwen3
quantization
4-bit precision
Instructions to use Reza2kn/Higgs-Audio-v3-TTS-4bit-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Reza2kn/Higgs-Audio-v3-TTS-4bit-MLX with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Reza2kn/Higgs-Audio-v3-TTS-4bit-MLX")# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("Reza2kn/Higgs-Audio-v3-TTS-4bit-MLX", dtype="auto") - MLX
How to use Reza2kn/Higgs-Audio-v3-TTS-4bit-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Higgs-Audio-v3-TTS-4bit-MLX Reza2kn/Higgs-Audio-v3-TTS-4bit-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
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