Instructions to use ronit33/intent-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ronit33/intent-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ronit33/intent-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ronit33/intent-classifier") model = AutoModelForSequenceClassification.from_pretrained("ronit33/intent-classifier") - Notebooks
- Google Colab
- Kaggle
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README.md
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model-index:
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- name: Intent Classifier with Deberta
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name: Text Classification
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type: text-classification
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metrics:
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- name: Accuracy
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model-index:
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- name: Intent Classifier with Deberta
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results:
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- task:
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- name: Text Classification
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- type: text-classification
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metrics:
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- name: Accuracy
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- type: accuracy
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- value: 0.996
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