Delete app.ipynb

app.ipynb

@@ -1,105 +0,0 @@
-!pip install -U "transformers==4.40.0" --upgrade
-!pip install -i https://pypi.org/simple/ bitsandbytes
-!pip install accelerate
-
-
-import transformers
-import torch
-
-model_id = "unsloth/llama-3-8b-Instruct-bnb-4bit"
-
-pipeline = transformers.pipeline(
-    "text-generation",
-    model=model_id,
-    model_kwargs={
-        "torch_dtype": torch.float16,
-        "quantization_config": {"load_in_4bit": True},
-        "low_cpu_mem_usage": True,
-    },
-)
-
-messages = [
-    {"role"   : "system",
-     "content": "You are an interviewer testing the user whether he can be a good manager or not. When the user says hi there!, i want you to begin"},
-    {"role"   : "user",
-     "content": """hi there!"""},
-]
-
-prompt = pipeline.tokenizer.apply_chat_template(
-        messages,
-        tokenize=False,
-        add_generation_prompt=True
-)
-
-terminators = [
-    pipeline.tokenizer.eos_token_id,
-    pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
-]
-
-outputs = pipeline(
-    prompt,
-    max_new_tokens=256,
-    eos_token_id=terminators,
-    do_sample=True,
-    temperature=0.6,
-    top_p=0.9,
-)
-
-print(outputs[0]["generated_text"][len(prompt):])
-
-!pip install gradio
-
-import gradio as gr
-
-messages = [{"role"   : "system",
-     "content": "You are an interviewer testing the user whether he can be a good manager or not. When the user says hi there!, i want you to begin"},
-    {"role"   : "user",
-     "content": """hi there!"""},]
-
-def add_text(history, text):
-    global messages  #message[list] is defined globally
-    history = history + [(text,'')]
-    messages = messages + [{"role":'user', 'content': text}]
-    return history, ''
-
-def generate(history):
-  global messages
-  prompt = pipeline.tokenizer.apply_chat_template(
-        messages,
-        tokenize=False,
-        add_generation_prompt=True
-)
-
-  terminators = [
-    pipeline.tokenizer.eos_token_id,
-    pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
-]
-
-  outputs = pipeline(
-    prompt,
-    max_new_tokens=256,
-    eos_token_id=terminators,
-    do_sample=True,
-    temperature=0.6,
-    top_p=0.9,
-)
-  response_msg = outputs[0]["generated_text"][len(prompt):]
-  for char in response_msg:
-      history[-1][1] += char
-      yield history
-  pass
-
-with gr.Blocks() as demo:
-
-    chatbot = gr.Chatbot(value=[], elem_id="chatbot")
-    with gr.Row():
-            txt = gr.Textbox(
-                show_label=False,
-                placeholder="Enter text and press enter",
-            )
-
-    txt.submit(add_text, [chatbot, txt], [chatbot, txt], queue=False).then(
-            generate, inputs =[chatbot,],outputs = chatbot,)
-
-demo.queue()
-demo.launch(debug=True)