Instructions to use nadika/complaints_classification_nepali with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nadika/complaints_classification_nepali with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nadika/complaints_classification_nepali")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nadika/complaints_classification_nepali") model = AutoModelForSequenceClassification.from_pretrained("nadika/complaints_classification_nepali", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fdfba276c48561a7d6aaf3852016cdcdeceb84b0d3d44bf5fc8d6f1f19281fa8
- Size of remote file:
- 4.86 kB
- SHA256:
- 683257102c7eb2cc418492fd7ce3cd9a433f1fa868d9c09ae34543becaa615c9
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