Text Classification
Transformers
PyTorch
ONNX
Arabic
bert
hate-speech
gender-based-violence
arabic
multiclass-classification
pilot
Eval Results (legacy)
text-embeddings-inference
Instructions to use thejosango/nuha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thejosango/nuha with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thejosango/nuha")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thejosango/nuha") model = AutoModelForSequenceClassification.from_pretrained("thejosango/nuha") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43ee7d56bc936ac7cd4ec29f14d0f33aca99e479ef121d9c027eeea839b601b0
- Size of remote file:
- 314 MB
- SHA256:
- d0f3499293186d4718646d31ed44bd78d64681b13ee29c83d23a380b284660da
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.