Instructions to use Dinusha-Ekanayake/predictix-ticket_categorization_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dinusha-Ekanayake/predictix-ticket_categorization_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Dinusha-Ekanayake/predictix-ticket_categorization_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Dinusha-Ekanayake/predictix-ticket_categorization_model") model = AutoModelForSequenceClassification.from_pretrained("Dinusha-Ekanayake/predictix-ticket_categorization_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| library_name: transformers | |
| pipeline_tag: text-classification | |
| language: | |
| - en | |
| base_model: | |
| - typeform/distilbert-base-uncased-mnli | |