Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use optimum/roberta-large-finetuned-clinc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use optimum/roberta-large-finetuned-clinc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="optimum/roberta-large-finetuned-clinc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("optimum/roberta-large-finetuned-clinc") model = AutoModelForSequenceClassification.from_pretrained("optimum/roberta-large-finetuned-clinc") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
#4 opened over 2 years ago
by
librarian-bot
Add evaluation results on clinc_oos dataset
3
#1 opened almost 4 years ago
by
autoevaluator