sadanand1120

vLLM CLI Arguments Parser

A Python script to automatically scrape vLLM serve command documentation and generate a clean YAML configuration file with all available flags and their default values.

Features

• 🌐 Auto-scrapes latest vLLM documentation
• 🧹 Clean parsing - removes symbols, handles multiple flag variants
• 📝 YAML output with inline comments and descriptions
• 📊 Progress bar with rich library

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High level process

• completely format your external ssd into ntfs using your gist's instructions
• install virtual box on ubuntu host (get the deb for the latest virtualbox from official site)
  • check the box for guest additions install
• install vbox extensions pack from official site. Then Tools -> EXtensions -> Install, to install that.
• add your user to vboxusers group (this allows usb sharing access inside machine)
• setup a win10 machine on virtualbox
  • add the external ssd to the shared device inside the USB tab of machine settings
  • install halseo wintousb tool in it
• get the win10 iso by going to "download win10 iso", downloading that tool, getting the iso file

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Completely format a USB, SSD from ubuntu

• lsblk and check the mount point, e.g., /dev/sda which might have different partitions like /dev/sda1 etc
• sudo umount /dev/sda*. Use sudo umount -l /dev/sda* if something refuses to unmount
• sudo fdisk /dev/sda to delete all partitions one-by-one:
  • Press p to print the current partitions
  • Press d to delete each partition (repeat for all).
  • Press w to write changes and exit.
  • HINT: just keep doing d until you get no partitions remaining to be deleted, then do w and exit.
• sudo parted /dev/sda mklabel gpt to create a new GPT partition table
• sudo parted -a optimal /dev/sda mkpart primary 0% 100% creates a new parition (/dev/sda1)

sadanand1120

import warnings
warnings.filterwarnings('ignore', category=FutureWarning)
import tensorflow as tf

text = tf.constant("Successfull Installation")
with tf.compat.v1.Session() as sess:
  print(sess.run(text))

sadanand1120

absl-py >= 0.7.0
astunparse == 1.6.3
gast == 0.3.3
google_pasta >= 0.1.8
h5py >= 2.10.0, < 2.11.0
keras_preprocessing >= 1.1.1, < 1.2
numpy >= 1.16.0, < 1.19.0
opt_einsum >= 2.3.2
protobuf >= 3.9.2
tensorboard >= 2.2.0, < 2.3.0

sadanand1120