Update README.md

README.md

@@ -88,12 +88,8 @@ MIT License — free to use, modify, and share.
 from transformers import pipeline
 
 # 📢 Start demo
-print("\n🔤 Masked Language Model (MLM) Demo")
-
-# 🧠 Load masked language model : eg boltuix/bert-lite
 mlm_pipeline = pipeline("fill-mask", model="boltuix/bert-lite")
 
-# ✍️ Masked sentences
 masked_sentences = [
     "The robot can [MASK] the room in minutes.",
     "He decided to [MASK] the project early.",
@@ -103,9 +99,8 @@ masked_sentences = [
     "Please [MASK] the door before leaving.",
 ]
 
-# 🤖 Predict missing words
 for sentence in masked_sentences:
-    print(f"\nInput: {sentence}")
+    print(f"Input: {sentence}")
     predictions = mlm_pipeline(sentence)
     for pred in predictions[:3]:
         print(f"✨ → {pred['sequence']} (score: {pred['score']:.4f})")
@@ -115,35 +110,51 @@ for sentence in masked_sentences:
 ---
 
 
-## 🔤 Masked Language Model (MLM) Demo
-
-Input: The robot can [MASK] the room in minutes.  
-✨ → The robot can clean the room in minutes. (score: 0.3124)  
-✨ → The robot can scan the room in minutes. (score: 0.1547)  
-✨ → The robot can paint the room in minutes. (score: 0.0983)  
-
-Input: He decided to [MASK] the project early.  
-✨ → He decided to finish the project early. (score: 0.3876)  
-✨ → He decided to start the project early. (score: 0.2109)  
-✨ → He decided to abandon the project early. (score: 0.0765)  
-
-Input: This device is [MASK] for small tasks.  
-✨ → This device is perfect for small tasks. (score: 0.2458)  
-✨ → This device is great for small tasks. (score: 0.1894)  
-✨ → This device is useful for small tasks. (score: 0.1321)  
-
-Input: The weather will [MASK] by tomorrow.  
-✨ → The weather will improve by tomorrow. (score: 0.2987)  
-✨ → The weather will change by tomorrow. (score: 0.1765)  
-✨ → The weather will clear by tomorrow. (score: 0.1034)  
-
-Input: She loves to [MASK] in the garden.  
-✨ → She loves to work in the garden. (score: 0.3542)  
-✨ → She loves to play in the garden. (score: 0.1986)  
-✨ → She loves to relax in the garden. (score: 0.0879)  
-
-Input: Please [MASK] the door before leaving.  
-✨ → Please close the door before leaving. (score: 0.4673)  
-✨ → Please lock the door before leaving. (score: 0.3215)  
-✨ → Please open the door before leaving. (score: 0.0652)  
-
+## 🔤 Masked Language Model (MLM)'s Output
+
+Input: The robot can [MASK] the room in minutes.
+✨ → the robot can leave the room in minutes. (score: 0.1608)
+✨ → the robot can enter the room in minutes. (score: 0.1067)
+✨ → the robot can open the room in minutes. (score: 0.0498)
+Input: He decided to [MASK] the project early.
+✨ → he decided to start the project early. (score: 0.1503)
+✨ → he decided to continue the project early. (score: 0.0812)
+✨ → he decided to leave the project early. (score: 0.0412)
+Input: This device is [MASK] for small tasks.
+✨ → this device is used for small tasks. (score: 0.4118)
+✨ → this device is useful for small tasks. (score: 0.0615)
+✨ → this device is required for small tasks. (score: 0.0427)
+Input: The weather will [MASK] by tomorrow.
+✨ → the weather will be by tomorrow. (score: 0.0980)
+✨ → the weather will begin by tomorrow. (score: 0.0868)
+✨ → the weather will come by tomorrow. (score: 0.0657)
+Input: She loves to [MASK] in the garden.
+✨ → she loves to live in the garden. (score: 0.3112)
+✨ → she loves to stay in the garden. (score: 0.0823)
+✨ → she loves to be in the garden. (score: 0.0796)
+Input: Please [MASK] the door before leaving.
+✨ → please open the door before leaving. (score: 0.3421)
+✨ → please shut the door before leaving. (score: 0.3208)
+✨ → please closed the door before leaving. (score: 0.0599)
+
+
+
+## 💡 Who's It For?
+👨‍💻 Developers: Lightweight NLP apps for mobile or IoT
+🤖 Innovators: Power wearables, smart homes, or robots
+🧪 Enthusiasts: Experiment on a budget
+🌿 Eco-Warriors: Reduce AI’s carbon footprint
+
+## 📈 Metrics That Matter
+✅ Accuracy: Competitive with larger models
+🎯 F1 Score: Balanced precision and recall
+⚡ Inference Time: Optimized for real-time use
+
+## 🧪 Trained On
+📘 Wikipedia
+📚 BookCorpus
+🧾 MNLI (Multi-Genre NLI)
+🔗 sentence-transformers/all-nli
+
+## 🔖 Tags
+#tiny-bert #iot #wearable-ai #intent-detection #smart-home #offline-assistant #nlp #transformers