Text Classification
Transformers
Safetensors
English
roberta
customer-support
support-tickets
helpdesk
zendesk
ticket-classification
customer-service
conversation-classification
Synthetic
text-embeddings-inference
Instructions to use aitrainingdatabroker/support-ticket-outcome-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aitrainingdatabroker/support-ticket-outcome-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aitrainingdatabroker/support-ticket-outcome-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aitrainingdatabroker/support-ticket-outcome-classifier") model = AutoModelForSequenceClassification.from_pretrained("aitrainingdatabroker/support-ticket-outcome-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
3 days ago
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Add source/cross_test.py
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Add source/train.py
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Add scores.json
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Add README.md
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Model weights and tokenizer
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initial commit
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