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# Install necessary libraries
# !pip install gradio huggingface_hub requests
import gradio as gr
import requests
import os
from huggingface_hub import HfApi, HfFolder
def download_and_upload(download_url, hf_write_token, model_name):
# Get the file name
file_name = download_url.split("/")[-1]
save_path = file_name
# Download the file
try:
response = requests.get(download_url, stream=True)
response.raise_for_status()
with open(save_path, 'wb') as f:
for chunk in response.iter_content(chunk_size=8192):
f.write(chunk)
except requests.exceptions.RequestException as e:
return f"An error occurred while downloading the file: {e}"
# Upload the file to Hugging Face
try:
api = HfApi()
HfFolder.save_token(hf_write_token)
api.upload_file(
path_or_fileobj=save_path,
path_in_repo=file_name, # Use the downloaded file name as is
repo_id=model_name,
repo_type="model"
)
return f"File successfully uploaded to {model_name}."
except Exception as e:
return f"An error occurred while uploading the file: {e}"
# Gradio Interface
with gr.Blocks() as demo:
gr.Markdown("# File Uploader")
download_url = gr.Textbox(label="Download URL", placeholder="Enter the file download link")
hf_write_token = gr.Textbox(label="Hugging Face Write Token", placeholder="Enter your Hugging Face write token", type="password")
model_name = gr.Textbox(label="Model Name", placeholder="Enter the model name (e.g., username/model_name)")
output = gr.Textbox(label="Output")
upload_button = gr.Button("Download and Upload")
upload_button.click(download_and_upload, inputs=[download_url, hf_write_token, model_name], outputs=output)
# Run the app
demo.launch()
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