XVilka

THIS GIST WAS MOVED TO TERMSTANDARD/COLORS REPOSITORY.

PLEASE ASK YOUR QUESTIONS OR ADD ANY SUGGESTIONS AS A REPOSITORY ISSUES OR PULL REQUESTS INSTEAD!

52cik

npm set registry https://r.npm.taobao.org # 注册模块镜像
npm set disturl https://npm.taobao.org/dist # node-gyp 编译依赖的 node 源码镜像

## 以下选择添加
npm set sass_binary_site https://npm.taobao.org/mirrors/node-sass # node-sass 二进制包镜像
npm set electron_mirror https://npm.taobao.org/mirrors/electron/ # electron 二进制包镜像
npm set ELECTRON_MIRROR https://cdn.npm.taobao.org/dist/electron/ # electron 二进制包镜像
npm set puppeteer_download_host https://npm.taobao.org/mirrors # puppeteer 二进制包镜像
npm set chromedriver_cdnurl https://npm.taobao.org/mirrors/chromedriver # chromedriver 二进制包镜像
npm set operadriver_cdnurl https://npm.taobao.org/mirrors/operadriver # operadriver 二进制包镜像

sagivo

to check if the server works - https://webrtc.github.io/samples/src/content/peerconnection/trickle-ice

stun:
stun.l.google.com:19302,
stun1.l.google.com:19302,
stun2.l.google.com:19302,
stun3.l.google.com:19302,
stun4.l.google.com:19302,
stun.ekiga.net,
stun.ideasip.com,

ad8e

/* Note: this Google copyright notice only applies to the original file, which has large sections copy-pasted here. my changes are under CC0 (public domain).

 * Copyright 2015 Google Inc.
 *
 * Use of this source code is governed by a BSD-style license that can be
 * found in the LICENSE file.
 */

/*
The official instructions don't work well. These alternative instructions are intended to be the shortest path to get a minimal setup running.

TheBloke

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
import torch

import os
import argparse

def get_args():
    parser = argparse.ArgumentParser()
    parser.add_argument("--base_model_name_or_path", type=str)

madebyollin

#!/usr/bin/env python3
from pathlib import Path
from safetensors.torch import load_file

def summarize_tensor(x):
    if x is None:
        return "None"
    x = x.float()
    return f"({x.min().item():.3f}, {x.mean().item():.3f}, {x.max().item():.3f})"

madebyollin

padeoe

🤗Huggingface Model Downloader

Note

(2026-06-18) Add 📊Download Progress, 🔁integrity-aware resume (re-fetch missing or changed files), and fast, resumable listing for 📚repos with massive file counts.
(2025-01-08) Add feature for 🏷️Tag(Revision) Selection, contributed by @Bamboo-D.
(2024-12-17) Add feature for ⚡Quick Startup and ⏭️Fast Resume, enabling skipping of downloaded files, while removing the git clone dependency to accelerate file list retrieval.

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 leverages curl and aria2c for fast and robust downloading of models and datasets.

Features

instr3

背景

• 日语音读的来源通常有汉音和吴音，吴音的例子较少
  • 当一个汉字有两个非常不同的音读时，通常意味着一个是汉音，另一个是吴音（如：頭：とう，ず）
• 普通话的来源基于北京方言，但是北京官话受到南京官话的强烈影响，以及各种外地人进入北京的影响，与中古汉语的对应会较为复杂。

• 翘舌音与失去的i：部分的翘舌音（如常）的古时韵母更接近于iang而非ang，而i后续被丢失。但是部分翘舌音本身就不带i（如山），因此情况较为复杂。在北京话中，“知庄章”这三组initial发音被合并成了翘舌音。“精”组变为平舌（不过中间不少颚化了，尖团合流）。在翘舌音的这三组中：
• 庄组比较排斥这种音，本来就没有 /i/ （如山）

madebyollin

Notes / Links about Stable Diffusion VAE

Stable Diffusion's VAE is a neural network that encodes images into a compressed "latent" format and decodes them back. The encoder performs 48x lossy compression, and the decoder generates new detail to fill in the gaps.

(Calling this model a "VAE" is sort of a misnomer - it's an encoder with some very slight KL regularization, and a conditional GAN decoder)

This document is a big pile of various links with more info.