I’ve been using Qwen 2.5 Coder (bartowski/Qwen2.5.1-Coder-7B-Instruct-GGUF) for some time now, and it has shown significant improvements compared to previous open weights models.
Notably, this is the first model that can be used with Aider. Moreover, Qwen 2.5 Coder has made notable strides in editing files without requiring frequent retries to generate in the proper format.
One area where most models struggle, including this one, is when the prompt exceeds a certain length. In this case, it appears that the model becomes unable to remember the system prompt when the prompt length is above ~2000 tokens.
Which backend are you using to run it, and does that backend have an option to adjust context size?
I noticed in LM Studio, for example, that the default context size is much smaller than the maximum that the model supports. Qwen should certainly support more than 2000 tokens. I’d try setting it to 32k if you can.
I have found the problem with the cut off, by default aider only sends 2048 tokens to ollama, this is why i have not noticed it anywhere else except for coding.
When running
/tokensin aider:$ 0.0000 16,836 tokens total 15,932 tokens remaining in context window 32,768 tokens max context window sizeEven though it will only send 2048 tokens to ollama.
To fix it i needed to add a file
.aider.model.settings.ymlto the repository:- name: aider/extra_params extra_params: num_ctx: 32768That’s because ollama’s default max ctx is 2048, as far as I know.