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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa05ef432687b36da121ec4e6c04fff77e588565067f2d2f6bc556c07b93da21
- Size of remote file:
- 1.35 GB
- SHA256:
- b785d92c3da4579f60d3335ce83d6f7f50c756dad9411f14c06bb44e2a8a2044
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