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from ctransformers import AutoModelForCausalLM
import gradio as gr
greety = """
A special thanks to the CCL AI team members who made a significant contribution to this project.
"""
llm = AutoModelForCausalLM.from_pretrained("pt_merge_model_v3.Q4_K_M.gguf",
model_type='llama',
max_new_tokens = 512,
threads = 3,
)
def stream(prompt, UL):
system_prompt = 'You are a helpful AI assistant'
prompt = f"<s>[INST]<<SYS>>\n + {system_prompt} + <</SYS>>\n{prompt.strip()}[/INST]"
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"],
["Explain what is atomic reaction"]
],
)
with gr.Blocks(css=css) as demo:
gr.HTML("<h1><center>RoyalGPT Free LLM Deployment Space<h1><center>")
gr.HTML("<h3><center><a href='https://royalgpt.xyz/'>RoyalGPT</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(share=True) |