Qwen35 toolkit

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Setup ​

NOTE

This setup is for the toolkit repository only. For training, use qwen-qlora-train.

Prerequisites ​

  • Arch Linux (or any Linux with NVIDIA driver)
  • Python 3.11
  • CUDA via driver (nvidia-smi works → CUDA is fine)

Steps ​

Step 1 — Create and activate a Python environment ​

Create an isolated environment before installing dependencies.

bash
yay -S python311
python3.11 -m venv venv
source venv/bin/activate

Success criteria: python --version points to your venv and Python 3.11.

Step 2 — Install toolkit dependencies and package ​

Install PyTorch first, then install the toolkit.

bash
# 1) PyTorch with CUDA (install before toolkit)
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu124

# 2a) Editable install (local clone)
pip install -e .

# 2b) Install directly from GitHub
pip install git+https://github.com/techwithsergiu/qwen35-toolkit.git

Success criteria: qwen35-convert --help prints CLI usage.

Step 3 — Authenticate with Hugging Face ​

Authenticate once for Hub download/upload operations.

bash
hf auth login

Success criteria: protected model/repo access works without extra prompts.

Expected result ​

  • Toolkit commands are available in shell (qwen35-*).
  • You can run local commands and access HF Hub.

Common failures ​

  • nvidia-smi not found -> install/fix NVIDIA driver first.
  • qwen35-...: command not found -> reactivate venv and reinstall package.
  • HF 401/403 errors -> rerun hf auth login or pass --hf-token.

Alternatively, pass --hf-token hf_... per command or set HF_TOKEN as an environment variable.