Instructions to use flax-community/mr-indicnlp-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flax-community/mr-indicnlp-classifier with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("flax-community/mr-indicnlp-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
4df6b08
1
Parent(s): e61e414
Update README.md
Browse files
README.md
CHANGED
|
@@ -4,11 +4,12 @@ This model was fine-tuned using [Marathi RoBERTa](https://huggingface.co/flax-co
|
|
| 4 |
## Dataset
|
| 5 |
IndicNLP Marathi news dataset consists 3 classes - `['lifestyle', 'entertainment', 'sports']` - with following docs distribution as per classes:
|
| 6 |
|
|
|
|
| 7 |
| train | eval | test |
|
| 8 |
| ----- | ---- | ---- |
|
| 9 |
| 9672 | 477 | 478 |
|
| 10 |
|
| 11 |
-
💯 Our
|
| 12 |
|
| 13 |
| Dataset | FT-W | FT-WC | INLP | iNLTK | **roberta-base-mr 🏆** |
|
| 14 |
| --------------- | ----- | ----- | ----- | ----- | --------------------- |
|
|
|
|
| 4 |
## Dataset
|
| 5 |
IndicNLP Marathi news dataset consists 3 classes - `['lifestyle', 'entertainment', 'sports']` - with following docs distribution as per classes:
|
| 6 |
|
| 7 |
+
|
| 8 |
| train | eval | test |
|
| 9 |
| ----- | ---- | ---- |
|
| 10 |
| 9672 | 477 | 478 |
|
| 11 |
|
| 12 |
+
💯 Our **`mr-indicnlp-classifier`** model fine tuned from **roberta-base-mr** Pretrained Marathi RoBERTa model outperformed both classifier mentioned in [Arora, G. (2020). iNLTK](https://www.semanticscholar.org/paper/iNLTK%3A-Natural-Language-Toolkit-for-Indic-Languages-Arora/5039ed9e100d3a1cbbc25a02c82f6ee181609e83/figure/3) and [Kunchukuttan, Anoop et al. AI4Bharat-IndicNLP.](https://www.semanticscholar.org/paper/AI4Bharat-IndicNLP-Corpus%3A-Monolingual-Corpora-and-Kunchukuttan-Kakwani/7997d432925aff0ba05497d2893c09918298ca55/figure/4)
|
| 13 |
|
| 14 |
| Dataset | FT-W | FT-WC | INLP | iNLTK | **roberta-base-mr 🏆** |
|
| 15 |
| --------------- | ----- | ----- | ----- | ----- | --------------------- |
|