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:
- dfc672bfd8e838851e46e20656fb27ec3b9884b851f1ab4b0ea32874f2c9d3f8
- Size of remote file:
- 4.73 kB
- SHA256:
- 3362a979a2de33cace3c19980bf3c8089f40091d67aedd6016a680feaaffbaf6
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