Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use rcade/finetuned-bert-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rcade/finetuned-bert-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rcade/finetuned-bert-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rcade/finetuned-bert-mrpc") model = AutoModelForSequenceClassification.from_pretrained("rcade/finetuned-bert-mrpc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 773cf5c2f82fbf531f712283daf263d444a91b7e4d4183f3bc09b3983b65717e
- Size of remote file:
- 433 MB
- SHA256:
- 2c5a659d8c225591b68b7192c81516478e1eb7caa6a79e538d820ab1f5d228b0
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