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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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example_title: "Neutral - #1"
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- text: "Where are Netflix's headquarters located?"
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example_title: "Neutral - #2"
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example_title: "Neutral - #1"
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example_title: "Neutral - #2"
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# deberta-v3-base-financial-question-classification
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Soon...
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