Instructions to use l3cube-pune/marathi-topic-medium-doc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/marathi-topic-medium-doc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="l3cube-pune/marathi-topic-medium-doc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/marathi-topic-medium-doc") model = AutoModelForSequenceClassification.from_pretrained("l3cube-pune/marathi-topic-medium-doc") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -21,11 +21,13 @@ More details on the dataset, models, and baseline results can be found in our [p
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@
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title={
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author={Joshi, Raviraj},
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```
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```
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@inproceedings{mittal2023l3cube,
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title={L3Cube-MahaNews: News-Based Short Text and Long Document Classification Datasets in Marathi},
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author={Mittal, Saloni and Magdum, Vidula and Hiwarkhedkar, Sharayu and Dhekane, Omkar and Joshi, Raviraj},
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booktitle={International Conference on Speech and Language Technologies for Low-resource Languages},
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pages={52--63},
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year={2023},
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organization={Springer}
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}
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```
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