Text Classification
Transformers
PyTorch
TensorBoard
English
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use JeremiahZ/roberta-base-qqp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JeremiahZ/roberta-base-qqp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JeremiahZ/roberta-base-qqp")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeremiahZ/roberta-base-qqp") model = AutoModelForSequenceClassification.from_pretrained("JeremiahZ/roberta-base-qqp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator
Beep boop, I am a bot from Hugging Face's automatic model evaluator 👋! We've added a new `verifyToken` field to your evaluation results to verify that they are produced by the model evaluator. Accept this PR to ensure that your results remain listed as **verified** on the [Hub leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards).d69b727
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Add evaluation results on the qqp config of glue (#1)
JeremiahZ +1: autoevaluator - Add evaluation results on the qqp config of glue (6ac1079c8aa854a88500b93f48d6206e5e90f94b) Co-authored-by: Evaluation Bot <autoevaluator@users.noreply.huggingface.co>6687715
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update model card README.md
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End of training
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initial commit
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