Update app.py

app.py

@@ -2,8 +2,29 @@ import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 # Specify the path to your fine-tuned model and tokenizer
-model_path = "./"  # Assuming the model is in the same directory as your notebook
-model_name = "https://huggingface.co/spaces/DR-Rakshitha/wizardlm_api/blob/main/pytorch_model-00001-of-00002.bin"  # Replace with your model name
+# model_path = "./"  # Assuming the model is in the same directory as your notebook
+# model_name = "https://huggingface.co/spaces/DR-Rakshitha/wizardlm_api/blob/main/pytorch_model-00001-of-00002.bin"  # Replace with your model name
+
+from llama_cpp import Llama 
+import timeit
+
+# Load Llama 2 model
+llm = Llama(model_path="./pytorch_model-00001-of-00002.bin",
+            n_ctx=512,
+            n_batch=128)
+
+# Start timer
+start = timeit.default_timer()
+
+# Generate LLM response
+# prompt = "What is Python?"
+
+# output = llm(prompt,
+#              max_tokens=-1,
+#              echo=False,
+#              temperature=0.1,
+#              top_p=0.9)
+
 
 # Load the model and tokenizer
 model = AutoModelForCausalLM.from_pretrained(model_path)
@@ -11,10 +32,16 @@ tokenizer = AutoTokenizer.from_pretrained(model_path)
 
 # Define the function for text generation
 def generate_text(input_text):
-    input_ids = tokenizer(input_text, return_tensors="pt").input_ids
-    output = model.generate(input_ids, max_length=50, num_return_sequences=1)
-    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
-    return generated_text
+    # input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+    # output = model.generate(input_ids, max_length=50, num_return_sequences=1)
+    # generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+    # return generated_text
+
+    output = llm(input_text,
+             max_tokens=-1,
+             echo=False,
+             temperature=0.1,
+             top_p=0.9)
 
 # Create the Gradio interface
 text_generation_interface = gr.Interface(