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:
- 72c1c75741c6f7bb54790a35bc16e2de3a6e636b9d054ea3827bdea9c42704d0
- Size of remote file:
- 499 MB
- SHA256:
- e0c645b896d784d9f04a33b6dc6a7474058a7ac4263f5c7047bffaeabe4b1f0d
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