Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use JeremiahZ/roberta-base-rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JeremiahZ/roberta-base-rte with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JeremiahZ/roberta-base-rte")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeremiahZ/roberta-base-rte") model = AutoModelForSequenceClassification.from_pretrained("JeremiahZ/roberta-base-rte") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4d1c76106b56d43fcb3c524778c5cc25eed0bb9cac90f54e3f51c6a41063404
- Size of remote file:
- 3.31 kB
- SHA256:
- e55420be4e32185a9ae24c70aad6c9592ee0a4300ee6891f062beb0ade3adfce
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