Create app.py

app.py

@@ -0,0 +1,50 @@
+import os
+import gradio as gr
+import ctransformers
+
+configObj = ctransformers.Config(stop=["\n", 'User'], context_length=2048)
+config = ctransformers.AutoConfig(config=configObj, model_type='llama')
+config.config.stop = ["\n"]
+
+# path_to_llm = os.path.abspath("llama-2-7b-chat.ggmlv3.q4_1.bin")
+
+llm = ctransformers.AutoModelForCausalLM.from_pretrained("TheBloke/Llama-2-7b-Chat-GGUF", model_file="llama-2-7b-chat.Q4_K_M.gguf", config=config)
+
+def complete(prompt, stop=["User", "Assistant"]):
+  tokens = llm.tokenize(prompt)
+  output = ''
+  for token in llm.generate(tokens):
+    result = llm.detokenize(token)
+    output += result
+    for word in stop:
+      if word in output:
+        print('\n')
+        return output
+    print(result, end='',flush=True)
+
+  print('\n')
+  return output
+
+title = "llama2-7b-chat-ggml"
+description = "This space is an attempt to run the GGUF 4 bit quantized version of 'llama2-7b-chat' on a CPU"
+
+example_1 = "Write a 7 line poem on AI"
+example_2 = "Tell me a joke"
+
+examples = [example_1, example_2]
+
+def generate_response(user_input):
+    prompt = f'User: {user_input}\nAssistant: '
+    response = complete(prompt)
+    return response
+
+UI = gr.Interface(
+    fn=generate_response,
+    inputs=gr.Textbox(label="User Query", placeholder="Ask your queries here...."),
+    outputs=gr.Textbox(label="Assistant Response"),
+    title=title,
+    description=description,
+    examples=examples
+)
+
+UI.launch()