Laz4rz

Ok, thanks for the tip but none of these helped. Or maybe first? It is now working without run limits. What I did after the initial changes: 1. tried ```...

Restarted everything. What seems to be fixing the issue reproductively is: 1. Deactivating Conda 2. DISABLE_COMPILER_CACHE=1 3. Run by pointing to the exact bin of native python with tinygrad installed...

Hey, yes of course it is run id dependent, but for now this is just not cohere. There is no reason the --run-id to be first Huggy2 and then Huggy...

Doing this: > > Try a `cxx11abiFALSE` version 试用版本 `cxx11abiFALSE` > > You can use this to solve the problem. Use pip to install the version package that matches yours...

You can check Skalski's work with PaliGemma here: https://github.com/roboflow/notebooks/blob/main/notebooks/how-to-finetune-paligemma-on-detection-dataset.ipynb Also google published Jax tutorial for paligemma finetuned captioning: https://ai.google.dev/gemma/docs/paligemma/fine-tuning-paligemma I played some with the captioning tutorial and would happily help...

When specifying source in dependencies and then specifying separate source in uv.sources — as to have a prod/dev uv sync --no-sources/uv sync separation -- uv doesn't correctly resolve dependencies of...

Just doing ```conda install -c conda-forge asteval``` fixes the issue.

workaround and issue: https://github.com/Deep-Learning-Profiling-Tools/triton-viz/issues/34