Delete app.py

app.py

@@ -1,50 +0,0 @@
-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("ToonTownTommy/llama2-7b-chat-hf-GGML", model_file="llama2-7b-chat-hf-GGML", 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()