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from threading import Thread
from llama_cpp import Llama
import torch
import gradio as gr
import re
torch_device = "cuda" if torch.cuda.is_available() else "cpu"
print("Running on device:", torch_device)
print("CPU threads:", torch.get_num_threads())
llm = Llama(model_path = 'Llama-2-ko-7B-chat-gguf-q4_0.bin',
n_ctx=100,
n_threads = 8,
n_batch = 100
)
def gen(x, max_new_tokens):
output = llm(f"Q: {x} A: ", max_tokens=max_new_tokens, stop=["Q:", "\n"], echo=True)
return output['choices'][0]['text'].replace('▁',' ')
def reset_textbox():
return gr.update(value='')
with gr.Blocks() as demo:
gr.Markdown(
"duplicated from beomi/KoRWKV-1.5B, baseModel:Llama-2-ko-7B-chat-gguf-q4_0"
)
with gr.Row():
with gr.Column(scale=4):
user_text = gr.Textbox(
placeholder='우리 여행 갈래?',
label="User input"
)
model_output = gr.Textbox(label="Model output", lines=10, interactive=False)
button_submit = gr.Button(value="Submit")
with gr.Column(scale=1):
max_new_tokens = gr.Slider(
minimum=1, maximum=200, value=20, step=1, interactive=True, label="Max New Tokens",
)
button_submit.click(gen, [user_text, max_new_tokens], model_output)
demo.queue(max_size=32).launch(enable_queue=True) |