Text Classification
Transformers
Safetensors
English
bert
intent-classification
customer-support
banking
banking77
Eval Results (legacy)
text-embeddings-inference
Instructions to use functionX86/banking77-intent-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use functionX86/banking77-intent-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="functionX86/banking77-intent-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("functionX86/banking77-intent-classifier") model = AutoModelForSequenceClassification.from_pretrained("functionX86/banking77-intent-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
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