Instructions to use shsha0110/bert-base-multilingual-cased-based-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shsha0110/bert-base-multilingual-cased-based-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="shsha0110/bert-base-multilingual-cased-based-encoder")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("shsha0110/bert-base-multilingual-cased-based-encoder") model = AutoModelForMaskedLM.from_pretrained("shsha0110/bert-base-multilingual-cased-based-encoder") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:914b36b39748c22dad594f85609876fc7f192226f7be9fd05f34bd8dc4c69fea
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size 711437136
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