Text-to-Speech
Transformers
Safetensors
higgs_multimodal_qwen3
feature-extraction
speech-generation
voice-agent
expressive-speech
controllable-tts
multilingual-tts
custom_code
Instructions to use rajarshisomvanshi/higgs-audio-v3-tts-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rajarshisomvanshi/higgs-audio-v3-tts-4b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="rajarshisomvanshi/higgs-audio-v3-tts-4b", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rajarshisomvanshi/higgs-audio-v3-tts-4b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31ae936f4198dce7424ae2cf8f4ce8e73fc75a4bbfbaff64a1e083145bd4d6fe
- Size of remote file:
- 9.31 GB
- SHA256:
- 2f7965264c360b38180885006944aa16bd1de20f4e6cff79f6473bfcf8ae3d5a
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