Instructions to use IIIT-L/indic-bert-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/indic-bert-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/indic-bert-finetuned-non-code-mixed-DS")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIIT-L/indic-bert-finetuned-non-code-mixed-DS") model = AutoModelForSequenceClassification.from_pretrained("IIIT-L/indic-bert-finetuned-non-code-mixed-DS") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a8735508eaa1c288d25b9dcb204fc34f78823bed45a7c05a2ac7ecfbba890f91
- Size of remote file:
- 3.38 kB
- SHA256:
- cc7d9722f189937b7f3e92218a1e06d4b041d182643617861b7c4491b3e12ffb
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