Text Classification
Transformers
PyTorch
Safetensors
deberta-v2
multilingual-sentiment-analysis
sentiment-analysis
aspect-based-sentiment-analysis
deberta
pyabsa
efficient
lightweight
production-ready
no-llm
Instructions to use yangheng/deberta-v3-base-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-base-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-base-absa-v1.1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yangheng/deberta-v3-base-absa-v1.1") model = AutoModelForSequenceClassification.from_pretrained("yangheng/deberta-v3-base-absa-v1.1") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
#6 opened 6 months ago
by
ViolettaY
Update tokenizer_config.json
#5 opened 6 months ago
by
ViolettaY
Fine-tuning using transformers trainer
❤️👍 3
15
#2 opened about 3 years ago
by
naif576
ValueError: Couldn't instantiate the backend tokenizer from one of
2
#1 opened about 3 years ago
by
David841130