Upload README.md

README.md

@@ -81,7 +81,7 @@ Using this model becomes easy when you have [sentence-transformers](https://www.
 pip install -U sentence-transformers
 ```
 
-Then you can use the model like this:
+### Embeddings
 
 ```python
 from sentence_transformers import SentenceTransformer
@@ -92,10 +92,57 @@ embeddings = model.encode(sentences)
 print(embeddings)
 ```
 
+### Usage Example
+
+```sh
+from sentence_transformers import SentenceTransformer, util
+import torch
+
+# Define sentences in Hausa
+sentences = [
+    "Menene sunan babban birnin Ingila?",
+    "Wanne dabba ne mafi zafi a duniya?",
+    "Ta yaya zan iya koyon harshen Hausa?",
+    "Wanne abinci ne mafi shahara a Najeriya?",
+    "Wane irin kaya ake sawa don bikin Hausa?"
+]
+
+# Load the Hausa-trained model
+model = SentenceTransformer('path/to/pmmlv2-fine-tuned-hausa')
+
+# Compute embeddings
+embeddings = model.encode(sentences, convert_to_tensor=True)
+
+# Function to find the closest sentence
+def find_closest_sentence(query_embedding, sentence_embeddings, sentences):
+    # Compute cosine similarities
+    cosine_scores = util.pytorch_cos_sim(query_embedding, sentence_embeddings)[0]
+    # Find the position of the highest score
+    best_match_index = torch.argmax(cosine_scores).item()
+    return sentences[best_match_index], cosine_scores[best_match_index].item()
+
+query = "Menene sunan babban birnin Ingila?"
+query_embedding = model.encode(query, convert_to_tensor=True)
+closest_sentence, similarity_score = find_closest_sentence(query_embedding, embeddings, sentences)
+
+print(f"Tambaya: {query}")
+print(f"Jimla mafi kusa: {closest_sentence}")
+print(f"Alamar kama: {similarity_score:.4f}")
+
+# You can also try with a new sentence not in the original list
+new_query = "Wanne sarki ne yake mulkin Kano a yanzu?"
+new_query_embedding = model.encode(new_query, convert_to_tensor=True)
+closest_sentence, similarity_score = find_closest_sentence(new_query_embedding, embeddings, sentences)
+
+print(f"\nSabuwar Tambaya: {new_query}")
+print(f"Jimla mafi kusa: {closest_sentence}")
+print(f"Alamar kama: {similarity_score:.4f}")
+```
+
 ### License
 
 This project is licensed under the [MIT License](./LICENSE).
 
 ### Copyright
 
-(c) 2024 [Finbarrs Oketunji](https://finbarrs.eu).
+(c) 2024 [Finbarrs Oketunji](https://finbarrs.eu).