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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeremiahZ/roberta-base-rte") model = AutoModelForSequenceClassification.from_pretrained("JeremiahZ/roberta-base-rte", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from JeremiahZ/roberta-base-rte: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/JeremiahZ/roberta-base-rte/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://JeremiahZ/roberta-base-rte@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/JeremiahZ/roberta-base-rte/resolve/refs%2Fpr%2F1/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.