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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=40, | |
n_threads = 8, | |
n_batch = 5 | |
) | |
def gen(x, max_new_tokens): | |
output = llm(f"### 명령어:\n{x}\n\n### 응답:", max_tokens=max_new_tokens, stop=["###"], 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) |