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
File size: 641 Bytes
81e8ada | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | #!/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()
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