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Source channel @githubtrending · Post #15263 · Nov 2

#python#deep_learning#inference#llm#nlp#pytorch#transformer Nano-vLLM is a small, fast, and easy-to-understand tool for running large language models offline. It matches the speed of bigger systems like vLLM but uses only about 1,200 lines of clean Python code, making it simple to read and modify. It includes smart features like prefix caching and tensor parallelism to boost performance. You can install it easily and run models like Qwen3-0.6B on your own GPU. This tool is great if you want fast, efficient AI inference without complex setups, ideal for learning, research, or small deployments on limited hardware. https://github.com/GeeeekExplorer/nano-vllm

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djangoproject

@djangoproject · Post #595 · 04/17/2018, 03:51 PM

https://github.com/pypa/virtualenv/issues/1059 Earlier today I installed python3.6 on my debian machine. Python3.6 was made available in buster distribution. When I try to create a virtualenv with python3.6. python3.6 -m venv venv gives the following error. The #virtual_environment was not created successfully because ensurepip is not available. On Debian/Ubuntu systems, you need to install the python3-venv package using the following command. apt-get install python3-venv You may need to use sudo with that command. After installing the python3-venv package, recreate your virtual environment. Failing command: ['/home/float/test/t/bin/python3.6', '-Im', 'ensurepip', '--upgrade', '--default-pip'] I do have python3-venv (3.5.3-1) installed. Why do I get this error? If I run the command py3 -Im ensurepip —upgrade —default-pip it says /usr/bin/python3.6: No module named ensurepip I don't have trouble creating virtualenvs using the default python3 version (3.5.3). Also , I noticed that I can create a virtualenv as follows: #virtualenv -p python3.6 #venv

djangoproject

@djangoproject · Post #535 · 12/28/2017, 10:12 AM

https://docs.pipenv.org/ #Pipenv — the officially recommended #Python#packaging tool from Python.org, free (as in freedom). Pipenv is a tool that aims to bring the best of all packaging worlds (#bundler, #composer, #npm, #cargo, #yarn, etc.) to the Python world. #Windows is a first–class citizen, in our world. It automatically creates and manages a #virtualenv for your projects, as well as adds/removes #packages from your #Pipfile as you install/uninstall packages. It also generates the ever–important Pipfile.lock, which is used to produce deterministic builds.