readme: ---
  tags:
  - fastai
  - text-classification
  
  widget:
  - text: "ഓഹരി വിപണി തകരുമ്പോള്‍ നിക്ഷേപം എങ്ങനെ സുരക്ഷിതമാക്കാം"
    example_title: "Malayalam News Classifier"
  
  ---
  
  
  # Malayalam (മലയാളം) Classifier using fastai (Working in Progress)
  
  🥳 This model is my attempt to use machine learning using Malayalam Language. Huge inspiration from [Malayalam Text Classifier](https://kurianbenoy.com/2022-05-30-malayalamtext-0/). Courtesy to @waydegilliam for [blurr](https://ohmeow.github.io/blurr/text-examples-multilabel.html)
  
  🌈 മലയാളത്തിൽ മെഷീൻ ലീർണിങ് പഠിക്കാനും പിന്നേ പരിചയപ്പെടാനും, to be continued...
  
  # How its built ? & How to use ? 
  
  Please find the [notebook](https://nbviewer.org/github/rajeshradhakrishnanmvk/kitchen2.0/blob/feature101-frontend/ml/fastai_X_Hugging_Face_Group_2022.ipynb) used for training the model
  
  Usage:
  
  First, install the utilities to load the model as well as `blurr`, which was used to train this model.
  
  ```bash
  !pip install huggingface_hub[fastai]
  !git clone https://github.com/ohmeow/blurr.git && cd blurr && pip install -e ".[dev]"
  ```
  
  ```python
  from huggingface_hub import from_pretrained_fastai
  learner = from_pretrained_fastai("rajeshradhakrishnan/ml-news-classify-fastai")
  
  
  sentences = ["ഓഹരി വിപണി തകരുമ്പോള്‍ നിക്ഷേപം എങ്ങനെ സുരക്ഷിതമാക്കാം",
               "വാര്‍ണറുടെ ഒറ്റക്കയ്യന്‍ ക്യാച്ചില്‍ അമ്പരന്ന് ക്രിക്കറ്റ് ലോകം"]
  
  probs = learner.predict(sentences)
  # 'business', 'entertainment', 'sports', 'technology'
  for idx in range(len(sentences)):
    print(f"Probability that sentence '{sentences[idx]}' is business is: {100*probs[idx]['probs'][0]:.2f}%")
    print(f"Probability that sentence '{sentences[idx]}' is entertainment is: {100*probs[idx]['probs'][1]:.2f}%")
    print(f"Probability that sentence '{sentences[idx]}' is sports is: {100*probs[idx]['probs'][2]:.2f}%")
    print(f"Probability that sentence '{sentences[idx]}' is technology is: {100*probs[idx]['probs'][3]:.2f}%")
  
  ```
  
  ---
  
  
  # Model card
  
  ## Model description
  The is a Malayalam classifier model for labels 'business', 'entertainment', 'sports', 'technology'.
  
  ## Intended uses & limitations
  The model can be used to categorize malayalam new sfeed.
  
  ## Training and evaluation data
  
  Data is from the [AI4Bharat-IndicNLP Dataset](https://github.com/AI4Bharat/indicnlp_corpus#indicnlp-news-article-classification-dataset) and wrapper to extract only Malayalam data( [HF dataset](https://huggingface.co/datasets/rajeshradhakrishnan/malayalam_news))!.
  
  ## Citation
  
  
  ```
  @article{kunchukuttan2020indicnlpcorpus,
      title={AI4Bharat-IndicNLP Corpus: Monolingual Corpora and Word Embeddings for Indic Languages},
      author={Anoop Kunchukuttan and Divyanshu Kakwani and Satish Golla and Gokul N.C. and Avik Bhattacharyya and Mitesh M. Khapra and Pratyush Kumar},
      year={2020},
      journal={arXiv preprint arXiv:2005.00085},
  }
  ```