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")# 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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac17a3e0cfb35a9111d5c74edd4c24b548de1965f80635c6682647b4e27781d4
- Size of remote file:
- 5.33 kB
- SHA256:
- 52248beebc82ce64db30d5f1c760e26f29144f5135e24bb3f43745abc4af3be3
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