Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use jiiyy/bert_multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jiiyy/bert_multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jiiyy/bert_multilingual")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jiiyy/bert_multilingual") model = AutoModelForSequenceClassification.from_pretrained("jiiyy/bert_multilingual") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8fdcbe547964a94727c057a77c1949828dc38c78e42f44508e1feaef091193fa
- Size of remote file:
- 711 MB
- SHA256:
- 675c49a36103b42f35d0f7468c016e71cbf209bccca69c075d7f91b0f46a4684
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