Update README.md

README.md

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----
-license: apache-2.0
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+
+# **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-roberta`** model. The fill-mask task predicts the most likely token(s) to replace the `[MASK]` token in a given sentence.
+
+---
+
+## **Setup**
+
+### **1. Clone the Repository**
+
+```bash
+git clone https://github.com/your-username/khasi-fill-mask.git
+cd khasi-fill-mask
+```
+
+### **2. Install Dependencies**
+
+Ensure you have Python 3.7 or later installed and the required libraries:
+
+```bash
+pip install transformers torch
+```
+
+If you intend to use GPU acceleration, ensure CUDA is installed on your system, and you have a compatible version of PyTorch.
+
+---
+
+## **Usage**
+
+### **1. Import Dependencies**
+
+```python
+from transformers import pipeline, AutoTokenizer
+```
+
+### **2. Initialize the Model and Tokenizer**
+
+Load the tokenizer and model pipeline:
+
+```python
+# Initialisation
+tokenizer = AutoTokenizer.from_pretrained('jefson08/kha-roberta')
+fill_mask = pipeline(
+    "fill-mask",
+    model="jefson08/kha-roberta",
+    tokenizer=tokenizer,
+    device="cuda",  # Use "cuda" for GPU or omit for CPU
+)
+```
+
+### **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})")
+```
+
+---
+
+## **Example Output**
+
+Given the input sentence:
+
+```plaintext
+"Nga dei u briew u ba [MASK] bha."
+```
+
+The model might output:
+
+```plaintext
+[{'score': 0.09230164438486099,
+  'token': 6086,
+  'token_str': 'mutlop',
+  'sequence': 'Nga dei u briew u ba  mutlop bha.'},
+ {'score': 0.051360130310058594,
+  'token': 2059,
+  'token_str': 'stad',
+  'sequence': 'Nga dei u briew u ba  stad bha.'},
+ {'score': 0.045497000217437744,
+  'token': 1864,
+  'token_str': 'khuid',
+  'sequence': 'Nga dei u briew u ba  khuid bha.'},
+ {'score': 0.04180142655968666,
+  'token': 668,
+  'token_str': 'kham',
+  'sequence': 'Nga dei u briew u ba  kham bha.'},
+ {'score': 0.027332570403814316,
+  'token': 2817,
+  'token_str': 'khlaiñ',
+  'sequence': 'Nga dei u briew u ba  khlaiñ bha.'}]
+```
+
+---
+
+## **Model Information**
+
+The `jefson08/kha-roberta` 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.
+
+---
+
+## **Project Structure**
+
+```plaintext
+├── README.md                # Documentation
+├── example.py               # Example script for fill-mask task
+```
+
+---
+
+## **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
+```
+
+---
+
+## **Acknowledgements**
+
+- Hugging Face [Transformers](https://huggingface.co/docs/transformers) library.
+- Model by [jefson08](https://huggingface.co/jefson08/kha-roberta).
+
+---
+
+## **License**
+
+This project is licensed under the MIT License. See the [LICENSE](./LICENSE) file for more details.
+
+---