README.md

# **Khasi Fill-Mask Model**

This project demonstrates how to use the Hugging Face Transformers library to perform a fill-mask task using the **`jefson08/kha-bert`** model. The fill-mask task predicts the most likely token(s) to replace the `[MASK]` token in a given sentence.

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## **Usage**

### **1. Import Dependencies**

```python
from transformers import pipeline
```

### **2. Initialize the Model and Tokenizer**

Load the tokenizer and model pipeline:

```python
# Initialisation
fill_mask = pipeline(
    "fill-mask",
    model="jefson08/kha-bert",
    tokenizer='jefson08/kha-bert'
)
```

### **3. Predict the [MASK] Token**

Provide a sentence with a `[MASK]` token for prediction:

```python
# Predict [MASK] token
sentence = "Nga dei u briew u ba [MASK] bha."
predictions = fill_mask(sentence)

# Display predictions
for prediction in predictions:
    print(f"{prediction['sequence']} (score: {prediction['score']:.4f})")
```

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## **Example Output**

Given the input sentence:

```plaintext
"Nga dei u briew u ba [MASK] bha."
```

The model might output:

```plaintext
[{'score': 0.05552137270569801,
  'token': 668,
  'token_str': 'kham',
  'sequence': 'Nga dei u briew u ba  kham bha.'},
 {'score': 0.03611050173640251,
  'token': 2318,
  'token_str': 'kmen',
  'sequence': 'Nga dei u briew u ba  kmen bha.'},
 {'score': 0.029321255162358284,
  'token': 3612,
  'token_str': 'tbit',
  'sequence': 'Nga dei u briew u ba  tbit bha.'},
 {'score': 0.028406640514731407,
  'token': 1860,
  'token_str': 'ieit',
  'sequence': 'Nga dei u briew u ba  ieit bha.'},
 {'score': 0.027690021321177483,
  'token': 4187,
  'token_str': 'sarong',
  'sequence': 'Nga dei u briew u ba  sarong bha.'}]
```

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## **Model Information**

The `jefson08/kha-bert` model is fine-tuned for Khasi text tasks. It uses the fill-mask pipeline to predict and replace `[MASK]` tokens in sentences, providing insights into contextual language understanding.

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## **Dependencies**

- [Transformers](https://huggingface.co/docs/transformers): Provides the pipeline and model-loading utilities.
- [PyTorch](https://pytorch.org/): Backend framework for running the model.

Install the dependencies with:

```bash
pip install transformers torch
```

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## **Acknowledgements**

- Hugging Face [Transformers](https://huggingface.co/docs/transformers) library.
- Model by [N Donald Jefferson Thabah](https://huggingface.co/jefson08/kha-roberta).

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## **License**

This project is licensed under the MIT License. See the [LICENSE](./LICENSE) file for more details.

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