Instructions to use Ashwini1412/nepali_complaints_classification_muril with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ashwini1412/nepali_complaints_classification_muril with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ashwini1412/nepali_complaints_classification_muril")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ashwini1412/nepali_complaints_classification_muril") model = AutoModelForSequenceClassification.from_pretrained("Ashwini1412/nepali_complaints_classification_muril") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a93498c787fff2064f4cc32a187853868e20c468d745c484f7e1ef2345d6dfb2
- Size of remote file:
- 4.86 kB
- SHA256:
- d8e8fec64f1dc656d7e1081356074fb93e4bc91bbdd3f8fa5b163f2ed82fa76c
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