Text Classification
Transformers
PyTorch
Safetensors
deberta-v2
Generated from Trainer
calibration
uncertainty
Instructions to use parameterlab/apricot_binary_trivia_qa_deberta-v3-base_for_gpt-3.5-turbo-0125 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use parameterlab/apricot_binary_trivia_qa_deberta-v3-base_for_gpt-3.5-turbo-0125 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="parameterlab/apricot_binary_trivia_qa_deberta-v3-base_for_gpt-3.5-turbo-0125")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("parameterlab/apricot_binary_trivia_qa_deberta-v3-base_for_gpt-3.5-turbo-0125") model = AutoModelForSequenceClassification.from_pretrained("parameterlab/apricot_binary_trivia_qa_deberta-v3-base_for_gpt-3.5-turbo-0125") - Notebooks
- Google Colab
- Kaggle