Update README.md

README.md

@@ -4,11 +4,17 @@ language:
 - am
 ---
 ### Model Description
-This is a fine-tuned version of Sentence-BERT (SBERT) for the Amharic language. The model was trained on a dataset of Natural Language Inference (NLI) examples in the Amharic language.
+This is a fine-tuned version of Sentence-BERT (SBERT) specifically designed for the Amharic language. It was trained on a Natural Language Inference (NLI) dataset written in the Amharic language. The model outputs sentence embeddings, which are numerical representations of sentences in the form of 768-dimensional vectors. 
 
 ### Usage
-This can be used as input to other machine learning models for downstream tasks such as Sentiment Analysis, Named Entity Recognition, etc.
-// enter code here
+This model can be used as input for downstream tasks such as sentiment analysis, recommendation systems, question answering, text summarization, named entity recognition, etc.
+
+```
+from sentence_transformers import SentenceTransformer
+
+SentenceModel = SentenceTransformer('heran/SBERT-am-finetune')
+textEncoding = SentenceModel.encode("ዛሬ አየሩ በጣም ጥሩ ነው።")
+```
 
 ### Limitations and Known Issues
-The model was trained on a limited dataset. It may include biases and may not perform well for sentences that include less used words.  
+It is important to note that the model was trained on a limited dataset, which means it may have inherent biases and may not perform optimally for sentences that contain infrequently used words. It is recommended to carefully evaluate the model's output and consider supplementing it with additional training data or methods to mitigate these limitations.