Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use autoevaluate/glue-qqp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoevaluate/glue-qqp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="autoevaluate/glue-qqp")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("autoevaluate/glue-qqp") model = AutoModelForSequenceClassification.from_pretrained("autoevaluate/glue-qqp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add evaluation results on the qqp config of glue
Beep boop, I am a bot from Hugging Face's automatic model evaluator 👋!\ Your model has been evaluated on the qqp config of the [glue](https://huggingface.co/datasets/glue) dataset by @lewtun, using the predictions stored [here](https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-glue-4805e982-13995915).\ 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/model-evaluator?dataset=glue).92ffcc4
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update model card README.md
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Training in progress, epoch 5
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Training in progress, epoch 4
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Training in progress, epoch 3
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Training in progress, epoch 2
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Training in progress, epoch 1
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initial commit
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