Text Classification
Transformers
PyTorch
Safetensors
deberta-v2
sentiment-analysis
aspect-based-sentiment-analysis
deberta
pyabsa
efficient
lightweight
production-ready
no-llm
Instructions to use yangheng/deberta-v3-large-absa-v1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yangheng/deberta-v3-large-absa-v1.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yangheng/deberta-v3-large-absa-v1.1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yangheng/deberta-v3-large-absa-v1.1") model = AutoModelForSequenceClassification.from_pretrained("yangheng/deberta-v3-large-absa-v1.1") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
Update README.md 7cc03a6 verified
Adding `safetensors` variant of this model (#1) 3ea8f1a
Update config.json b63ac5f
init 4183682
yangheng95 commited on