YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

Higgs Audio V2 Tokenizer

This is the tokenizer for the Higgs Audio V2 text-to-speech model.

Description

The Higgs Audio V2 Tokenizer handles text preprocessing and tokenization for the Higgs Audio V2 TTS model.

Model Details

  • Model Type: Text Tokenizer
  • Framework: HuggingFace Transformers
  • Purpose: Text preprocessing for TTS

Usage

from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("Toowired/higgs-v2-tokenizer")

# Tokenize text for TTS
text = "Hello, this is a test."
tokens = tokenizer(text, return_tensors="pt")

Features

  • Optimized for English text
  • Handles special characters and punctuation
  • Compatible with Higgs Audio V2 LLM
  • Fast tokenization for real-time applications

Intended Use

  • Text preprocessing for text-to-speech
  • Tokenization for Higgs Audio V2 model
  • Research in TTS preprocessing

Technical Details

  • Vocabulary size optimized for speech synthesis
  • Special tokens for audio markers
  • Efficient encoding/decoding

License

Please check the original model repository for license information.

Contact

For questions about this tokenizer, please contact the repository owner.

Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support