Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use DerivedFunction1/roberta-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DerivedFunction1/roberta-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DerivedFunction1/roberta-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DerivedFunction1/roberta-v2") model = AutoModelForSequenceClassification.from_pretrained("DerivedFunction1/roberta-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 546dbde412b80d4ccb21988abe199d000008d6d9cb2801ba89297ce2e5455ed5
- Size of remote file:
- 5.2 kB
- SHA256:
- 6e8e1ba81943820ea21a9aed375cdd9415d1a993aac7f1e8159055bd510a26b5
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