Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use rendchevi/roberta-base-pr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rendchevi/roberta-base-pr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rendchevi/roberta-base-pr")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rendchevi/roberta-base-pr") model = AutoModelForSequenceClassification.from_pretrained("rendchevi/roberta-base-pr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d7202172cf520627bce8f608313139380243079b228870851ad45568b59fae8
- Size of remote file:
- 5.84 kB
- SHA256:
- c676d300fe5a974a53f90454df43a12fe5615810d045797e05acc591c0db4ef4
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