wadeKeith/autoresearch-qwen
Autonomous Qwen3-VL training-code research on the official DocVQA benchmark. main: NVIDIA multi-GPU, mlx: Apple Silicon/MPS.
- Stars
- 212
- Forks
- 34
- Open issues
- 0
- Last push
- 4mo ago
autoresearch-qwen star history
+0 this week
About autoresearch-qwen
autoresearch-qwen is a free, open-source AI agent tool by wadeKeith, written mainly in Python. Autonomous Qwen3-VL training-code research on the official DocVQA benchmark. main: NVIDIA multi-GPU, mlx: Apple Silicon/MPS. It has 212 GitHub stars and 34 forks, and was last updated 4mo ago. It's released under the MIT license, a standard open-source license. According to the project, it works on macOS.
- License
- MIT
- Commercial use
- Commercial OK
- Language
- Python
- Stars
- 212
- Last update
- 4mo ago
- Runs on Mac
- Yes (as stated by the project)
- GPU
- Not stated
- Paid API key
- Not required
- Self-hostable
- Not stated
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autoresearch-qwen FAQ
Can I use autoresearch-qwen commercially?
Yes. MIT is a permissive license: commercial use is allowed as long as you keep the license notice. This is a plain-English summary, not legal advice.
Is autoresearch-qwen free?
Yes. autoresearch-qwen is open source and free to use. It's released under the MIT license, a standard open-source license.
Does autoresearch-qwen run on a Mac?
Yes. According to the project, autoresearch-qwen works on macOS.
Does autoresearch-qwen need a GPU?
The project doesn't state hardware needs. AI models generally run much faster with a GPU.
Is autoresearch-qwen still maintained?
It was last updated 4mo ago. Check recent issues on GitHub to judge how active it is.
What are alternatives to autoresearch-qwen?
Similar free, open-source tools include AutoGPT, langflow, hermes-agent, mem0.
Maintain autoresearch-qwen?
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