Instructions to use IIIT-L/hing-mbert-finetuned-non-code-mixed-DS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIIT-L/hing-mbert-finetuned-non-code-mixed-DS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="IIIT-L/hing-mbert-finetuned-non-code-mixed-DS")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIIT-L/hing-mbert-finetuned-non-code-mixed-DS") model = AutoModelForSequenceClassification.from_pretrained("IIIT-L/hing-mbert-finetuned-non-code-mixed-DS") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e84eb5886266dc60f98112c307882dce57255207a1af80eeddf7e90e93ee6b22
- Size of remote file:
- 3.38 kB
- SHA256:
- 7d1a0d0c139830917dce36e27fd7d74c5218df41e1339be08092203b154f2b80
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