Update app.py

app.py

@@ -9,19 +9,23 @@ tokenizer = AutoTokenizer.from_pretrained(model_id)
 
 def chat(question):
     prompt = f"### Instruction: {question}\n### Response:"
-
     inputs = tokenizer(prompt, return_tensors="pt")
-    output = model.generate(inputs["input_ids"], max_new_tokens=100)
-    
-    response = tokenizer.decode(output[0].tolist(), skip_special_tokens=True)
+    output = model.generate(inputs["input_ids"])
+    response = tokenizer.decode(output[0].tolist())
     print(response)
-    
     return response
 
 iface = gr.Interface(fn=chat,
                      inputs=gr.inputs.Textbox(label="Enter your text"),
                      outputs="text",
-                     title="Chat with Surrey County Council InfoBot")
+                     title="Chat with Raven")
 
 # index = construct_index("docs")
 iface.launch()
+
+
+
+### Instruction: How do I train the RWKV on specific data?
+### Response: To train the RWKV on specific data, you can use the `train_rwkv` 
+# function from the `sklearn.model_selection` module. 
+# This function takes a list of data points as input and returns a list of predictions for each data point. You can then use this list of predictions to train the RWKV on your specific data.