Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Sejan/bert-finetuned-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sejan/bert-finetuned-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sejan/bert-finetuned-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sejan/bert-finetuned-mrpc") model = AutoModelForSequenceClassification.from_pretrained("Sejan/bert-finetuned-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45e2efbfaac8d274af07868274862651bd60c2cdd384c1bd0b0b94722af0e4ca
- Size of remote file:
- 438 MB
- SHA256:
- 2b56a7d1047e31f51d4487cbafd94339d25ed99b52dafc7ed99ed9ffc8eead8f
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