from ctransformers import AutoModelForCausalLM import gradio as gr greety = """ Follow us [Gathnex](https://medium.com/@gathnex), [linkedin](https://www.linkedin.com/company/gathnex/) and [Github](https://github.com/gathnexadmin) for more update on Genrative AI, LLM,etc. A special thanks to the Gathnex team members who made a significant contribution to this project. """ llm = AutoModelForCausalLM.from_pretrained("zephyr-7b-beta.Q4_K_S.gguf", model_type='mistral', max_new_tokens = 1096, threads = 3, ) def stream(prompt, UL): system_prompt = 'You are a helpful AI assistant' E_INST = "" user, assistant = "<|user|>", "<|assistant|>" prompt = f"{system_prompt}{E_INST}\n{user}\n{prompt.strip()}{E_INST}\n{assistant}\n" return llm(prompt) css = """ h1 { text-align: center; } #duplicate-button { margin: auto; color: white; background: #1565c0; border-radius: 100vh; } .contain { max-width: 900px; margin: auto; padding-top: 1.5rem; } """ chat_interface = gr.ChatInterface( fn=stream, #additional_inputs_accordion_name = "Credentials", #additional_inputs=[ # gr.Textbox(label="OpenAI Key", lines=1), # gr.Textbox(label="Linkedin Access Token", lines=1), #], stop_btn=None, examples=[ ["explain Large language model"], ["what is quantum computing"] ], ) with gr.Blocks(css=css) as demo: gr.HTML("