Instructions to use l3cube-pune/marathi-tweets-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/marathi-tweets-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="l3cube-pune/marathi-tweets-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/marathi-tweets-bert") model = AutoModelForMaskedLM.from_pretrained("l3cube-pune/marathi-tweets-bert") - Notebooks
- Google Colab
- Kaggle
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@@ -11,9 +11,9 @@ More details on the dataset, models, and baseline results can be found in our [p
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Released under project: https://github.com/l3cube-pune/MarathiNLP
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```
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@article{
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title={Spread Love Not Hate: Undermining the Importance of Hateful Pre-training for Hate Speech Detection},
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author={
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journal={arXiv preprint arXiv:2210.04267},
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year={2022}
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}
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Released under project: https://github.com/l3cube-pune/MarathiNLP
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```
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@article{gokhale2022spread,
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title={Spread Love Not Hate: Undermining the Importance of Hateful Pre-training for Hate Speech Detection},
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author={Gokhale, Omkar and Kane, Aditya and Patankar, Shantanu and Chavan, Tanmay and Joshi, Raviraj},
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journal={arXiv preprint arXiv:2210.04267},
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year={2022}
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}
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