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import os | |
import shutil | |
import subprocess | |
import signal | |
os.environ["GRADIO_ANALYTICS_ENABLED"] = "False" | |
import gradio as gr | |
from huggingface_hub import create_repo, HfApi | |
from huggingface_hub import snapshot_download | |
from huggingface_hub import whoami | |
from huggingface_hub import ModelCard | |
from gradio_huggingfacehub_search import HuggingfaceHubSearch | |
from apscheduler.schedulers.background import BackgroundScheduler | |
HF_TOKEN = os.environ.get("HF_TOKEN") | |
HF_PATH = "https://huggingface.co/" | |
# change to include others | |
CONV_TEMPLATE = "tinyllama_v1_0" | |
def button_click(_, hf_model_id, quantization): | |
os.system("mkdir -p dist/models && cd dist/models") | |
os.system("git lfs install") | |
os.system("git clone " + HF_PATH + hf_model_id) | |
os.system("cd ../..") | |
return "successful" | |
demo = gr.Interface( | |
fn=button_click, | |
inputs = [gr.Button("Click me"), | |
gr.Textbox(label="HF Model ID"), | |
gr.Dropdown(["q4f16_1", "q4f32_1"], label="Quantization Method")], | |
outputs = "text" | |
) | |
demo.launch() |