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import os
import gradio as gr
import copy
from llama_cpp import Llama
from huggingface_hub import hf_hub_download
try:
llm = Llama(
model_path=hf_hub_download(
repo_id=os.environ.get("REPO_ID", "microsoft/Phi-3-mini-4k-instruct-gguf"),
filename=os.environ.get("MODEL_FILE", "Phi-3-mini-4k-instruct-q4.gguf"),
),
n_ctx=2048,
n_gpu_layers=-1, # change n_gpu_layers if you have more or less VRAM
)
except Exception as e:
print(e)
def generate_text(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
):
temp = ""
input_prompt = f"[INST] <<SYS>>\n{system_message}\n<</SYS>>\n\n "
for interaction in history:
input_prompt = (
input_prompt
+ str(interaction[0])
+ " [/INST] "
+ str(interaction[1])
+ " </s><s> [INST] "
)
input_prompt = input_prompt + str(message) + " [/INST] "
output = llm(
input_prompt,
temperature=temperature,
top_p=top_p,
top_k=40,
repeat_penalty=1.1,
max_tokens=max_tokens,
stop=[
"<|prompter|>",
"<|endoftext|>",
"<|endoftext|> \n",
"ASSISTANT:",
"USER:",
"SYSTEM:",
],
stream=True,
)
for out in output:
stream = copy.deepcopy(out)
temp += stream["choices"][0]["text"]
yield temp
demo = gr.ChatInterface(
generate_text,
title="llama-cpp-python on GPU",
description="Running LLM with https://github.com/abetlen/llama-cpp-python",
examples=[
["How to setup a human base on Mars? Give short answer."],
["Explain theory of relativity to me like I’m 8 years old."],
["What is 9,000 * 9,000?"],
["Write a pun-filled happy birthday message to my friend Alex."],
["Justify why a penguin might make a good king of the jungle."],
],
cache_examples=False,
retry_btn=None,
undo_btn="Delete Previous",
clear_btn="Clear",
additional_inputs=[
gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-p (nucleus sampling)",
),
],
)
if __name__ == "__main__":
demo.launch()
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