AlphaNext

🤗Huggingface Model Downloader

Considering the lack of multi-threaded download support in the official huggingface-cli, and the inadequate error handling in hf_transfer, this command-line tool smartly utilizes wget or aria2 for LFS files and git clone for the rest.

Features

⏯️ Resume from breakpoint: You can re-run it or Ctrl+C anytime.
🚀 Multi-threaded Download: Utilize multiple threads to speed up the download process.
🚫 File Exclusion: Use --exclude or --include to skip or specify files, save time for models with duplicate formats (e.g., *.bin or *.safetensors).
🔐 Auth Support: For gated models that require Huggingface login, use --hf_username and --hf_token to authenticate.
🪞 Mirror Site Support: Set up with HF_ENDPOINT environment variable.

Common Options

-#, --progress-bar Make curl display a simple progress bar instead of the more informational standard meter.

-b, --cookie <name=data> Supply cookie with request. If no =, then specifies the cookie file to use (see -c).

-c, --cookie-jar <file name> File to save response cookies to.

	# firstly, pip install pillow-avif-plugin Pillow

	from PIL import Image
	import pillow_avif
	import sys

	aviffile = sys.argv[1]
	avifImage = Image.open(aviffile)
	avifImage.save(aviffile.replace('avif', 'png'), 'png')

	import torch
	import pdb
	import numpy as np

	class Net(torch.nn.Module):
	def __init__(self, n_feature, n_output):
	super(Net, self).__init__()
	self.conv = torch.nn.Conv2d(n_feature, n_output, 1)
	def forward(self, x):
	x = self.conv(x)

	# solve bug in Github project : https://github.com/Wang-Tianwei/Decoupled-attention-network

	# method 0
	# could use readlines() and open file function, but remember that
	# your dicts variable format and your Chinese characters format

	##############################################################################################

	# method 1
	dict_file = open('char.U', 'r')

	#include <opencv2/opencv.hpp>
	#include <Magick++.h>
	#include <iostream>

	using namespace std;
	using namespace Magick;
	using namespace cv;
	// imageMagick installation on Mac OSX: https://www.sethvargo.com/install-imagemagick-on-osx-lion/
	// read gif's first frame to cv::Mat https://stackoverflow.com/questions/41841553/convert-magickimage-to-cvmat
	// ref link: https://imagemagick.org/discourse-server/viewtopic.php?t=35080

	#include <Eigen/Dense>
	#include <vector>
	#include <stdio.h>
	#include <iostream>
	using namespace Eigen;
	using namespace std;
	// Eigen is column major storage
	int main(){
	std::vector<Matrix<float, 2, 3> > batch_m;
	MatrixXf x(2,3);