Instructions to use l3cube-pune/marathi-sentiment-md with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/marathi-sentiment-md with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="l3cube-pune/marathi-sentiment-md")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/marathi-sentiment-md") model = AutoModelForSequenceClassification.from_pretrained("l3cube-pune/marathi-sentiment-md") - Notebooks
- Google Colab
- Kaggle
| language: mr | |
| tags: | |
| - bert | |
| license: cc-by-4.0 | |
| datasets: | |
| - L3Cube-MahaSent-MD | |
| widget: | |
| - text: "ते फुलांचे सौंदर्य आहे जे कवी आणि लेखकांना त्यांच्याजवळ इतके आकर्षित करते, आणि आपण ते त्यांच्या लेखना मधून बघू शकतात" | |
| ## MahaSent-MD | |
| MahaSent-MD is a MahaBERT(<a href="https://huggingface.co/l3cube-pune/marathi-bert-v2">l3cube-pune/marathi-bert-v2</a>) model fine-tuned on full L3Cube-MahaSent-MD Corpus, a multi-domain Marathi sentiment analysis dataset. <br> | |
| The MahaSent-MD dataset contains domains like movie reviews, generic tweets, subtitles, and political tweets. This model is trained on all the domains. <br> | |
| [dataset link] (https://github.com/l3cube-pune/MarathiNLP) | |
| More details on the dataset, models, and baseline results can be found in our [paper] (https://arxiv.org/abs/2306.13888) | |
| <br> | |
| Citing: | |
| ``` | |
| @article{pingle2023l3cube, | |
| title={L3Cube-MahaSent-MD: A Multi-domain Marathi Sentiment Analysis Dataset and Transformer Models}, | |
| author={Pingle, Aabha and Vyawahare, Aditya and Joshi, Isha and Tangsali, Rahul and Joshi, Raviraj}, | |
| journal={arXiv preprint arXiv:2306.13888}, | |
| year={2023} | |
| } | |
| ``` | |
| ``` | |
| @article{joshi2022l3cube, | |
| title={L3cube-mahanlp: Marathi natural language processing datasets, models, and library}, | |
| author={Joshi, Raviraj}, | |
| journal={arXiv preprint arXiv:2205.14728}, | |
| year={2022} | |
| } | |
| ``` | |
| Other Marathi Sentiment models from MahaSent family are shared here:<br> | |
| <a href="https://huggingface.co/l3cube-pune/marathi-sentiment-md"> MahaSent-MD (multi domain) </a> <br> | |
| <a href="https://huggingface.co/l3cube-pune/marathi-sentiment-tweets"> MahaSent-GT (generic tweets) </a> <br> | |
| <a href="https://huggingface.co/l3cube-pune/marathi-sentiment-movie-reviews"> MahaSent-MR (movie reviews) </a> <br> | |
| <a href="https://huggingface.co/l3cube-pune/marathi-sentiment-political-tweets"> MahaSent-PT (political tweets) </a> <br> | |
| <a href="https://huggingface.co/l3cube-pune/marathi-sentiment-subtitles"> MahaSent-ST (TV subtitles) </a> <br> | |
| <a href="https://huggingface.co/l3cube-pune/MarathiSentiment"> MahaSent v1 (political tweets) </a> <br> | |