Instructions to use ThivyanRR/english_seamlessm4t_medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThivyanRR/english_seamlessm4t_medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ThivyanRR/english_seamlessm4t_medium")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("ThivyanRR/english_seamlessm4t_medium") model = AutoModel.from_pretrained("ThivyanRR/english_seamlessm4t_medium") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 902242aac9a04ced868d808781c24e6756d5aeb426451698aad68d6f1858ab9b
- Size of remote file:
- 17.3 MB
- SHA256:
- f402521b10c5050f013fb3429177cef7b4352d503c0f24ed68a1c301256aa0dc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.