Update README.md

README.md

@@ -1,3 +1,63 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- SamirXR/NyX-Roleplay
+- Isotonic/human_assistant_conversation
+- itsahyadav/conversation.json
+- flammenai/character-roleplay-DPO
+- Seikaijyu/Classical-Chinese-Roleplay
+language:
+- en
+pipeline_tag: text-classification
+---
+
+This AI predicts if a text is roleplay or not (returns percentage).
+Created by NexusAI Join our discord server: https://discord.gg/7zvkzYutvF
+
+# How to use?
+
+```py
+from tensorflow import keras
+
+class RPClassifier:
+    def __init__(self, model_path='anti_rp.h5'):
+        self.model_path = model_path
+        self.model = None
+        self.load_model()
+
+    def load_model(self):
+        if self.model is None:
+            try:
+                self.model = keras.models.load_model(self.model_path)
+            except (FileNotFoundError, OSError):
+                raise Exception("Model file not found")
+
+    async def predict(self, text):
+        if not self.model:
+            raise Exception("Model not found")
+        try:
+            tokenizer = keras.preprocessing.text.Tokenizer()
+            tokenizer.fit_on_texts([text])
+            sequence = tokenizer.texts_to_sequences([text])
+            padded_sequence = keras.preprocessing.sequence.pad_sequences(sequence, maxlen=self.model.input_shape[1])
+            prediction = self.model.predict(padded_sequence)[0][0]
+            return prediction
+        except Exception as e:
+            raise Exception("Error occurred while predicting roleplay. {e}")
+
+    async def analyze(self, input_text):
+        rp_percentage = await self.predict(input_text)
+        return rp_percentage
+
+async def main():
+    classifier = RPClassifier()
+    while True:
+        input_text = input("> ")
+        if input_text.lower() == 'exit':
+            break
+        result = await classifier.analyze(input_text)
+        print(result)
+
+import asyncio
+asyncio.run(main()) 
+```