Text-to-Speech
GLM-TTS
Safetensors
Chinese
English
llm
tts
zero-shot
voice-cloning
reinforcement-learning
flow-matching
Instructions to use zai-org/GLM-TTS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLM-TTS
How to use zai-org/GLM-TTS with GLM-TTS:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Commit History
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Add `library_name` to metadata
Verified signatureThis PR enhances the model card by adding `library_name: transformers` to the metadata. This tag is justified by the `config.json` file, which specifies `"architectures": ["LlamaForCausalLM"]` and `"model_type": "llama"`. Llama-based models are typically integrated and used with the Hugging Face `transformers` library, enabling a predefined code snippet for users on the Hub. No sample usage code snippet has been added as the provided GitHub README does not contain a suitable Python example for programmatic inference via a library.43ab8ab -
Update README.md
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Add files using upload-large-folder tool
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initial commit
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