Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use SteveWCG/roberta-sentence-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SteveWCG/roberta-sentence-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SteveWCG/roberta-sentence-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SteveWCG/roberta-sentence-classifier") model = AutoModelForSequenceClassification.from_pretrained("SteveWCG/roberta-sentence-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ebef73472124221070ff8bf9f7b822b7d12133ec4d0cee78b95c5a9c521b2960
- Size of remote file:
- 5.84 kB
- SHA256:
- d33d862f34f14f1be3a5b401657088aad8258ab22ada4ef2a573fe88437b8e0d
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