Text Classification
Transformers
ONNX
Safetensors
Chinese
bert
chinese
intent-classification
text-embeddings-inference
Instructions to use pawizard/traffic-classify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pawizard/traffic-classify with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pawizard/traffic-classify")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pawizard/traffic-classify") model = AutoModelForSequenceClassification.from_pretrained("pawizard/traffic-classify", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e2a9e2da141fdb98cd387a3a11317ab90240ef7e5298aa4531fa727d8a2a079
- Size of remote file:
- 5.84 kB
- SHA256:
- 772ab76968477d5a4289da87bbdd0f254aef4a28339fe192732b6f0c3de8a847
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