Instructions to use Trat80/sfxking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Trat80/sfxking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Trat80/sfxking")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("Trat80/sfxking") model = AutoModelForTextToWaveform.from_pretrained("Trat80/sfxking") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForTextToWaveform
tokenizer = AutoTokenizer.from_pretrained("Trat80/sfxking")
model = AutoModelForTextToWaveform.from_pretrained("Trat80/sfxking")Quick Links
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Trat80/sfxking")