Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Cheng98/bert-base-qnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cheng98/bert-base-qnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cheng98/bert-base-qnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cheng98/bert-base-qnli") model = AutoModelForSequenceClassification.from_pretrained("Cheng98/bert-base-qnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload BertForSequenceClassification
Browse files- pytorch_model.bin +3 -0
pytorch_model.bin
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