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
File size: 463 Bytes
bccbc5b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | """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"]
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