Instructions to use Gem1832/super_07 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gem1832/super_07 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Gem1832/super_07")# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("Gem1832/super_07", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dfaa298c8a8f3789db99ca4ed93704b205026a77009243b49d7f8e194c368803
- Size of remote file:
- 11.4 MB
- SHA256:
- 09267689b8362020b9763b65dd5be7e086b31e28d72e02837a9e781de9a91bc7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.