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from ctransformers import AutoModelForCausalLM
import gradio as gr
greety = """
As a derivate work of [Linkedin Automation System](https://medium.com/@gathnex) by Gathnex,
Follow us on [linkedin](https://www.linkedin.com/company/gathnex/) and [Github](https://github.com/gathnexadmin). 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(user_prompt):
system_prompt = 'Below is an instruction that describes a task. Write a response that appropriately completes the request.'
E_INST = "</s>"
user, assistant = "<|user|>", "<|assistant|>"
prompt = f"{system_prompt}{E_INST}\n{user}\n{user_prompt.strip()}{E_INST}\n{assistant}\n"
for text in llm(prompt, stream=True, threads=3):
print(text, end="", flush=True)
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("<h1><center>Gathnex Linkedin Automation using Generative AI<h1><center>")
gr.HTML("<h3><center><a href='https://medium.com/@gathnex'>Gathnex AI</a>💬<h3><center>")
gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button")
chat_interface.render()
gr.Markdown(greety)
if __name__ == "__main__":
demo.queue(max_size=10).launch() |