Instructions to use IIIT-L/indic-bert-finetuned-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-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-code-mixed-DS")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("IIIT-L/indic-bert-finetuned-code-mixed-DS") model = AutoModelForSequenceClassification.from_pretrained("IIIT-L/indic-bert-finetuned-code-mixed-DS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from IIIT-L/indic-bert-finetuned-code-mixed-DS: direct link, hf CLI and curl.
- Browser
- Download file 15.3 MB
-
https://huggingface.co/IIIT-L/indic-bert-finetuned-code-mixed-DS/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://IIIT-L/indic-bert-finetuned-code-mixed-DS@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/IIIT-L/indic-bert-finetuned-code-mixed-DS/resolve/refs%2Fpr%2F1/tokenizer.json
15.3 MB
- Xet hash:
- e853ba8230303b4f4e0810c091f5a24a43f72ae5bc7acd5b15429b98862a84d9
- Size of remote file:
- 15.3 MB
- SHA256:
- ad28a51a2b8feb63cc054de5ec4bcb566c06c0d2941dcc68a94fff5e9708ca41
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