Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Cheng98/bert-base-rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cheng98/bert-base-rte with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cheng98/bert-base-rte")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cheng98/bert-base-rte") model = AutoModelForSequenceClassification.from_pretrained("Cheng98/bert-base-rte", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5aa7b57c3609d4ca294618ee3ea5b688b1eee1dc54aeb9dadbe645fdab97f0d
- Size of remote file:
- 433 MB
- SHA256:
- 16356d06adba81986ceed99f04f2450631db4ecebd4a4b724af40ab3a0fffc16
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