Instructions to use tugstugi/bert-large-mongolian-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tugstugi/bert-large-mongolian-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tugstugi/bert-large-mongolian-uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tugstugi/bert-large-mongolian-uncased") model = AutoModelForMaskedLM.from_pretrained("tugstugi/bert-large-mongolian-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tugstugi/bert-large-mongolian-uncased: direct link, hf CLI and curl.
- Browser
- Download file 1.35 GB
-
https://huggingface.co/tugstugi/bert-large-mongolian-uncased/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tugstugi/bert-large-mongolian-uncased/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tugstugi/bert-large-mongolian-uncased/resolve/main/pytorch_model.bin
1.35 GB
- Xet hash:
- 6cbf8522a0d0d4667fa8210286ffd1df3d7cec617a5209f81326c58968032419
- Size of remote file:
- 1.35 GB
- SHA256:
- 916fd15ba9a6a1205aaa137009fb7bee04ee6fbc933b43b65322b75edcb7bcab
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