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This GitHub repository provides a comprehensive guide on setting up a Conda environment tailored for Multi-Models or Large Language Models (LLMs). Whether you're working on machine learning projects, natural language processing, or any other data-intensive tasks, this environment setup ensures you have the necessary tools and dependencies in place.

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Conda Environment Setup for Multi-Models or LLMs

Installation

Manual installation using Conda

Recommended if you have some experience with the command-line.

0. Install Conda

https://docs.conda.io/en/latest/miniconda.html

1. Create a new conda environment

conda create -n llm_env python=3.11 -y
activate llm_env

2. Install Pytorch

System GPU Command
Linux/WSL NVIDIA pip install torch torchvision torchaudio
Linux/WSL CPU only pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
Linux AMD pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm5.4.2
MacOS + MPS Any pip install torch torchvision torchaudio
Windows NVIDIA pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117
Windows CPU only pip install torch torchvision torchaudio

The up-to-date commands can be found here: https://pytorch.org/get-started/locally/.

3. Install the web UI

curl -o req.txt https://github.com/raw/MaharshPatelX/conda-environment-multi-model/main/requirements.txt
pip install -r requirements.txt

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This GitHub repository provides a comprehensive guide on setting up a Conda environment tailored for Multi-Models or Large Language Models (LLMs). Whether you're working on machine learning projects, natural language processing, or any other data-intensive tasks, this environment setup ensures you have the necessary tools and dependencies in place.

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