Instructions to use garNER/bert-base-multilingual-cased-multi-LM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use garNER/bert-base-multilingual-cased-multi-LM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="garNER/bert-base-multilingual-cased-multi-LM")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("garNER/bert-base-multilingual-cased-multi-LM") model = AutoModelForTokenClassification.from_pretrained("garNER/bert-base-multilingual-cased-multi-LM") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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version https://git-lfs.github.com/spec/v1
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oid sha256:81e788260f79972a5a64e7f7b1c9c548347897d2673b01b3716a9e6bb30b7ecf
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size 709288104
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