Instructions to use IIIT-L/albert-base-v2-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/albert-base-v2-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/albert-base-v2-finetuned-non-code-mixed-DS")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIIT-L/albert-base-v2-finetuned-non-code-mixed-DS") model = AutoModelForSequenceClassification.from_pretrained("IIIT-L/albert-base-v2-finetuned-non-code-mixed-DS") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fea1a43bac4d85e30d57329a970bcfcee2c65a63b1530fb09e101e7f44c580bb
- Size of remote file:
- 3.38 kB
- SHA256:
- c3818dac7502d916d4c7003e568442172e8fe7c768d987190e248430f250909a
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