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: 558 Bytes
bccbc5b | 1 2 3 4 5 6 7 8 9 10 11 12 | # F5TTS_v1_Base | E2TTS_Base
model = "F5TTS_v1_Base"
ref_audio = "infer/examples/basic/basic_ref_en.wav"
# If an empty "", transcribes the reference audio automatically.
ref_text = "Some call me nature, others call me mother nature."
gen_text = "I don't really care what you call me. I've been a silent spectator, watching species evolve, empires rise and fall. But always remember, I am mighty and enduring."
# File with text to generate. Ignores the text above.
gen_file = ""
remove_silence = false
output_dir = "tests"
output_file = "infer_cli_basic.wav"
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