Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use autoevaluate/binary-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoevaluate/binary-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="autoevaluate/binary-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("autoevaluate/binary-classification") model = AutoModelForSequenceClassification.from_pretrained("autoevaluate/binary-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add evaluation results on glue
Beep boop, I am a bot from Hugging Face's automatic evaluation service! Your model has been evaluated on the [glue](https://huggingface.co/datasets/glue) dataset, using the predictions stored [here](https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-18d57ef1-c1f9-43cf-a48f-22510edbaf26-2221). Accept this pull request to see the results displayed on the [Hub leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=glue). Evaluate your model on more datasets [here](https://huggingface.co/spaces/autoevaluate/autoevaluate?dataset=glue).f4a218e
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Update README.md (#4)
- Update README.md (fdb90d596717933b064dd1ca6e18018f706c2bfc)57326b3
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Add cool new feature (#3)
- Add cool new feature (d208680fe1a7f01529cf739ecf14aebc3d12efa2)fbcfb7f -
add config
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Update README.md
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update model card README.md
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End of training
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Training in progress, epoch 1
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initial commit
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