Update README.md

README.md

@@ -28,6 +28,38 @@ tags:
 - **Model Size:** 80 - 250 million parameters
 - **Language Support:** Tshivenda, Nguni languages (Zulu, Xhosa, Swati), Sotho languages (Northern Sotho, Southern Sotho, Setswana), and Xitsonga.
 
+## Usage example(s)
+
+```python
+from transformers import pipeline
+
+# Initialize the pipeline for masked language model
+# Note: You might need to login, and request permissions to access dsfsi while the model is in private-beta
+unmasker = pipeline('fill-mask', model='dsfsi/zabantu-bantu-250m')
+
+
+sample_sentences = {
+    'zulu': "Le ndoda ithi izo____ ukudla.",  # Masked word for Zulu
+    'tshivenda': "Mufana uyo____ vhukuma.",  # Masked word for Tshivenda
+    'sepedi': "Mosadi o ____ pheka.",  # Masked word for Sepedi
+    'tswana': "Monna o ____ tsamaya.",  # Masked word for Tswana
+    'tsonga': "N'wana wa xisati u ____ ku tsaka."  # Masked word for Tsonga
+}
+
+
+for language, sentence in sample_sentences.items():
+    masked_sentence = sentence.replace('____', unmasker.tokenizer.mask_token)
+    # Get the model predictions
+    results = unmasker(masked_sentence)
+    print(f"Original sentence ({language}): {sentence}")
+    print(f"Top prediction for the masked token: {results[0]['sequence']}\n")
+```
+
+* For fine-tuning tasks, checkout these examples:
+  * [Text Classification]()
+  * [NER]()
+  * [POS]()
+
 
 ## Model Variants