Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use JeremiahZ/roberta-base-stsb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JeremiahZ/roberta-base-stsb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JeremiahZ/roberta-base-stsb")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeremiahZ/roberta-base-stsb") model = AutoModelForSequenceClassification.from_pretrained("JeremiahZ/roberta-base-stsb") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d40b1aeed55879ceddeac8ef9f196d6b313889156178b2cd8c606f628c8c0fec
- Size of remote file:
- 3.31 kB
- SHA256:
- 7983024ba7d9ab8fb923d0dad6386fe6b1f6a85268c4c449b1885c6938229975
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