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:
- bd7e966b71bf96ceeb358f8c04f5fc941bf75697afa4dbf739491d10590f3102
- Size of remote file:
- 3.64 kB
- SHA256:
- e3a8cdc0e0b08d0919e2a55d55ab5856e5ed80600791ca6cd3480df56df7cafc
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