Text Classification
Transformers
Safetensors
English
distilbert
bank user complaint
intent-classifier
Instructions to use KunalEsM/bank_complaint_intent_classifier_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KunalEsM/bank_complaint_intent_classifier_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KunalEsM/bank_complaint_intent_classifier_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KunalEsM/bank_complaint_intent_classifier_v2") model = AutoModelForSequenceClassification.from_pretrained("KunalEsM/bank_complaint_intent_classifier_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66dc04745a20cc3f2f147f91d1a4fe57775b012fc6e8c45b704fd74c8bed26ad
- Size of remote file:
- 268 MB
- SHA256:
- c4a1568a3c46d79c94ace1e75977fa0e62f50f34ea3b9e3c42c2ab98202d67f6
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