Update README.md

README.md

@@ -65,3 +65,39 @@ For a detailed example of how to load and use this model, please refer to the Co
 ## Ethical Considerations
 
 As with any language model, care should be taken when deploying this for real-world applications. Potential biases present in the training data could be reflected in the translations. It's important to monitor its output and ensure fair and accurate use.
+## 🚀 How to use
+
+```python
+from huggingface_hub import snapshot_download
+import tensorflow as tf
+import numpy as np
+import os
+from tensorflow.keras.preprocessing.text import tokenizer_from_json
+from tensorflow.keras.preprocessing.sequence import pad_sequences
+
+repo_id = "{repo_id}"
+local_dir = snapshot_download(repo_id=repo_id)
+
+model = tf.keras.models.load_model(os.path.join(local_dir, "Translation_model_for_hf.keras"))
+
+with open(os.path.join(local_dir, "tokenizer/eng_tokenizer.json"), "r", encoding="utf-8") as f:
+    eng_tokenizer = tokenizer_from_json(f.read())
+
+with open(os.path.join(local_dir, "tokenizer/ar_tokenizer.json"), "r", encoding="utf-8") as f:
+    ar_tokenizer = tokenizer_from_json(f.read())
+
+def translate(sentences):
+    seq = eng_tokenizer.texts_to_sequences(sentences)
+    padded = pad_sequences(seq, maxlen=model.input_shape[1], padding='post')
+    preds = model.predict(padded)
+    preds = np.argmax(preds, axis=-1)
+    
+    results = []
+    for s in preds:
+        text = [ar_tokenizer.index_word[i] for i in s if i != 0]
+        results.append(' '.join(text))
+    return results
+
+# Example
+print(translate(["Hello, how are you?"]))
+"""