Instructions to use SaherMuhamed/bert-intention-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaherMuhamed/bert-intention-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SaherMuhamed/bert-intention-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SaherMuhamed/bert-intention-classifier") model = AutoModelForSequenceClassification.from_pretrained("SaherMuhamed/bert-intention-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Create README.md
Browse files
README.md
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---
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## This project uses a fine-tuned BERT model that is an encoder only model without a decoder used to detect user intent from text inputs (e.g., chatbot queries).
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license: apache-2.0
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datasets:
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- clinc/clinc_oos
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metrics:
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- accuracy
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base_model:
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- google-bert/bert-base-uncased
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library_name: transformers
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tags:
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- finance
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- travel
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- banking
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- nlp
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