Instructions to use mohdali1/customer-support-ticket-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohdali1/customer-support-ticket-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mohdali1/customer-support-ticket-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mohdali1/customer-support-ticket-classifier") model = AutoModelForSequenceClassification.from_pretrained("mohdali1/customer-support-ticket-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0e0417628671196ed7ac3614fb0059fecfc3c4014c0cc1084d86d4b082a3284a
- Size of remote file:
- 298 Bytes
- SHA256:
- e925cf5869201b7ffeffed08df54923926faf8fe41fe2916485ca9204a0f2ca8
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