Instructions to use google/muril-large-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/muril-large-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="google/muril-large-cased")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("google/muril-large-cased") model = AutoModel.from_pretrained("google/muril-large-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc06154b226e7caa9026c780af01145871997aba350b0fb6dc601e4750056f24
- Size of remote file:
- 2.03 GB
- SHA256:
- 1a3bb993f09d053d285b7f301ddeef32934db4038593c7fc9eaa02c6057b27d0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.