Text Classification
Transformers
Safetensors
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use tmnam20/bert-base-multilingual-cased-rte-10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tmnam20/bert-base-multilingual-cased-rte-10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tmnam20/bert-base-multilingual-cased-rte-10")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tmnam20/bert-base-multilingual-cased-rte-10") model = AutoModelForSequenceClassification.from_pretrained("tmnam20/bert-base-multilingual-cased-rte-10") - Notebooks
- Google Colab
- Kaggle
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