Instructions to use tugstugi/bert-large-mongolian-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tugstugi/bert-large-mongolian-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tugstugi/bert-large-mongolian-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tugstugi/bert-large-mongolian-cased") model = AutoModelForMaskedLM.from_pretrained("tugstugi/bert-large-mongolian-cased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a11f0332ea0c9eb9d252246f06c9e991d907c2d33b04ab15596fd116da8fdd71
- Size of remote file:
- 1.35 GB
- SHA256:
- 57131075c31a642c115fe64c122f76613497c87055b265b513fdffb4789353f2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.