Text Classification
Transformers
PyTorch
English
deberta-v2
deberta-v3-base
natural-language-inference
pipeline
text-embeddings-inference
Instructions to use nogae/deberta-v3-base-financial-question-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nogae/deberta-v3-base-financial-question-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nogae/deberta-v3-base-financial-question-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nogae/deberta-v3-base-financial-question-classification") model = AutoModelForSequenceClassification.from_pretrained("nogae/deberta-v3-base-financial-question-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53e1d3ec2af114645ff850e60b8c82868fecce1bffdd058a8b11b5c9f0696e1e
- Size of remote file:
- 738 MB
- SHA256:
- 0d10b8d86f0c2b525b42b8bea8e2197c9d93ee691008a7871eeeea9983981a01
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