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import gradio as gr
import os
from pathlib import Path
import argparse
model_file = "Yi-6B.q4_k_m.gguf"
if not os.path.isfile("Yi-6B.q4_k_m.gguf"):
os.system("wget -c https://huggingface.co/SamPurkis/Yi-6B-GGUF/resolve/main/Yi-6B.q4_k_m.gguf")
DEFAULT_MODEL_PATH = model_file
parser = argparse.ArgumentParser()
parser.add_argument("-m", "--model", default=DEFAULT_MODEL_PATH, type=Path, help="model path")
parser.add_argument("--mode", default="chat", type=str, choices=["chat", "generate"], help="inference mode")
parser.add_argument("-l", "--max_length", default=2048, type=int, help="max total length including prompt and output")
parser.add_argument("-c", "--max_context_length", default=512, type=int, help="max context length")
parser.add_argument("--top_k", default=0, type=int, help="top-k sampling")
parser.add_argument("--top_p", default=0.7, type=float, help="top-p sampling")
parser.add_argument("--temp", default=0.95, type=float, help="temperature")
parser.add_argument("--repeat_penalty", default=1.1, type=float, help="penalize repeat sequence of tokens")
parser.add_argument("-t", "--threads", default=0, type=int, help="number of threads for inference")
parser.add_argument("--plain", action="store_true", help="display in plain text without markdown support")
args = parser.parse_args()
from pyllamacpp.model import Model
model = Model(model_path=model_file)
def predict(input, system_prompt, chatbot, max_length, ctx_length, top_p, temperature, history):
chatbot.append((input, ""))
response = ""
history.append(input)
generation_kwargs = dict(
max_length=max_length,
max_context_length=ctx_length,
do_sample=temperature > 0,
top_k=40,
top_p=top_p,
temperature=temperature,
repetition_penalty=1.1,
num_threads=0,
stream=True,
)
for response_piece in model.generate(input):
response += response_piece
chatbot[-1] = (chatbot[-1][0], response)
yield chatbot, history
history.append(response)
yield chatbot, history
def reset_user_input():
return gr.update(value="")
def reset_state():
return [], []
with gr.Blocks() as demo:
gr.HTML("""<h1 align="center">01-Yi 6B</h1>""")
chatbot = gr.Chatbot()
with gr.Row():
with gr.Column(scale=4):
system_prompt = gr.Textbox(show_label=False, placeholder="system prompt ...", lines=2)
user_input = gr.Textbox(show_label=False, placeholder="Input...", lines=6)
submitBtn = gr.Button("Submit", variant="primary")
with gr.Column(scale=1):
max_length = gr.Slider(0, 32048, value=args.max_length, step=1.0, label="Maximum Length", interactive=True)
ctx_length = gr.Slider(0, 4096, value=512, step=1.0, label="Maximum Context Length", interactive=True)
top_p = gr.Slider(0, 1, value=args.top_p, step=0.01, label="Top P", interactive=True)
temperature = gr.Slider(0, 1, value=args.temp, step=0.01, label="Temperature", interactive=True)
emptyBtn = gr.Button("Clear History")
history = gr.State([])
submitBtn.click(
predict, [user_input, system_prompt, chatbot, max_length, ctx_length, top_p, temperature, history], [chatbot, history], show_progress=True
)
submitBtn.click(reset_user_input, [], [user_input])
emptyBtn.click(reset_state, outputs=[chatbot, history], show_progress=True)
demo.queue().launch(share=False, inbrowser=True) |