Instructions to use dtorber/bert-base-multilingual-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/bert-base-multilingual-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dtorber/bert-base-multilingual-cased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dtorber/bert-base-multilingual-cased") model = AutoModelForSequenceClassification.from_pretrained("dtorber/bert-base-multilingual-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- model.safetensors +1 -1
- training_args.bin +1 -1
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