Instructions to use voidful/phoneme_bart_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/phoneme_bart_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="voidful/phoneme_bart_base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("voidful/phoneme_bart_base") model = AutoModel.from_pretrained("voidful/phoneme_bart_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12f6e022f5431109f0ae9d5f49a9002e2a98c6fadc85ed534637527b3452b2ef
- Size of remote file:
- 558 MB
- SHA256:
- 6e4fdb5e04114696ec4f7cc0cb5fc2a22a826f1c9eea234ca550b5390341a2fd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.