Text Classification
Transformers
Safetensors
English
distilbert
customer-support
intent-classification
support-tickets
Eval Results (legacy)
text-embeddings-inference
Instructions to use Janvi17/customer-support-ticket-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Janvi17/customer-support-ticket-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Janvi17/customer-support-ticket-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Janvi17/customer-support-ticket-classifier") model = AutoModelForSequenceClassification.from_pretrained("Janvi17/customer-support-ticket-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add comprehensive model card with evaluation, examples, limitations, and dataset attribution
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Fine-tuned DistilBERT for customer support ticket classification | Acc: 1.0000 | Macro F1: 1.0000
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Model save
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Training in progress, epoch 5
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Training in progress, epoch 1
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initial commit
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