Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use sgugger/finetuned-bert-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgugger/finetuned-bert-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sgugger/finetuned-bert-mrpc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sgugger/finetuned-bert-mrpc") model = AutoModelForSequenceClassification.from_pretrained("sgugger/finetuned-bert-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Align label mapping with mrpc config of glue dataset (#1)
- Align label mapping with mrpc config of glue dataset (89af331fc75273a908b31f8bcfeb55f2990ebf55) Co-authored-by: Lewis Tunstall <lewtun@users.noreply.huggingface.co>9c735e2
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Add second tokenizer for tests
b8f2adf
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add config
35024fa -
add model
3e55d72 -
initial commit
043f369