Instructions to use Renderlib-dev/sooktam2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Renderlib-dev/sooktam2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Renderlib-dev/sooktam2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Renderlib-dev/sooktam2", trust_remote_code=True, dtype="auto") - F5-TTS
How to use Renderlib-dev/sooktam2 with F5-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
| """HF Auto classes entrypoint for remote loading (used by AutoModel/AutoTokenizer).""" | |
| import os | |
| import sys | |
| _ROOT = os.path.dirname(os.path.abspath(__file__)) | |
| _SRC = os.path.join(_ROOT, "src") | |
| if _SRC not in sys.path: | |
| sys.path.insert(0, _SRC) | |
| from f5_tts.hf_auto import ( # noqa: E402 | |
| F5TTSConfig, | |
| F5TTSAutoModel, | |
| F5TTSTokenizer, | |
| register_f5tts_auto, | |
| ) | |
| __all__ = ["F5TTSConfig", "F5TTSAutoModel", "F5TTSTokenizer", "register_f5tts_auto"] | |