Text Classification
Transformers
Safetensors
Russian
customer-support
hierarchical-classification
mps
minilm
Instructions to use ZenMan67/support-ticket-classifiers-minilm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZenMan67/support-ticket-classifiers-minilm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ZenMan67/support-ticket-classifiers-minilm")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ZenMan67/support-ticket-classifiers-minilm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| #!/usr/bin/env python3 | |
| import argparse | |
| import json | |
| from hub_runtime import HubTicketClassifier | |
| def main() -> None: | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("text") | |
| parser.add_argument("--repo-id") | |
| parser.add_argument("--revision", default="main") | |
| parser.add_argument("--top-k", type=int, default=3) | |
| args = parser.parse_args() | |
| classifier = HubTicketClassifier( | |
| repo_id=args.repo_id, | |
| revision=args.revision, | |
| ) | |
| print(json.dumps( | |
| classifier.predict(args.text, args.top_k), | |
| ensure_ascii=False, | |
| indent=2, | |
| )) | |
| if __name__ == "__main__": | |
| main() | |