Instructions to use FrinzTheCoder/bert-base-multilingual-cased-orm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FrinzTheCoder/bert-base-multilingual-cased-orm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FrinzTheCoder/bert-base-multilingual-cased-orm")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FrinzTheCoder/bert-base-multilingual-cased-orm") model = AutoModelForSequenceClassification.from_pretrained("FrinzTheCoder/bert-base-multilingual-cased-orm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1de97505f09e8ea6ecff2d0ec5c2ab20836b2d67314b27556f841370b709e48a
- Size of remote file:
- 711 MB
- SHA256:
- 46f6fbb0578b7c2e8e4df627ca73be2ce7ece2bdd2c5c4881d73fa08961900bb
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