Text Classification
Transformers
PyTorch
Safetensors
English
distilbert
Generated from Trainer
finance
intent-classification
text-embeddings-inference
Instructions to use lxyuan/banking-intent-distilbert-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lxyuan/banking-intent-distilbert-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lxyuan/banking-intent-distilbert-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lxyuan/banking-intent-distilbert-classifier") model = AutoModelForSequenceClassification.from_pretrained("lxyuan/banking-intent-distilbert-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9854fdf453998ca8a9d19fd9f9a82823019d83197540c91ad9e863c939a87517
- Size of remote file:
- 268 MB
- SHA256:
- d9e4e38821bcaf06f7a5bce67ec08fbcbabffaa07724b9131d6156fdc5125607
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