Text Classification
Transformers
PyTorch
ONNX
Safetensors
Arabic
bert
hate-speech
gender-based-violence
arabic
trinary-classification
pilot
Eval Results (legacy)
text-embeddings-inference
Instructions to use thejosango/nuha-ajp-trinary-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thejosango/nuha-ajp-trinary-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thejosango/nuha-ajp-trinary-onnx")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thejosango/nuha-ajp-trinary-onnx") model = AutoModelForSequenceClassification.from_pretrained("thejosango/nuha-ajp-trinary-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 907b3d079509aa09014b6153a9859aa47ac055ffb40c74dcd59d0c228b59c143
- Size of remote file:
- 314 MB
- SHA256:
- 369fb710b83acca4ad3e7e08dfb30dcf9e044841ceddc31594d1610048ae58a6
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