Struggling to get a Gemma‑3 model running with JAX, Tunix and GRPO in a notebook? The most common roadblocks are messy dependency installs, missing Hugging Face tokens, GPU‑vs‑CPU mismatches, and having to restart the runtime after a big install. Here’s a quick, step‑by‑step fix that gets you from a blank Colab notebook to a training loop in under ten minutes.
First, run a single cell that checks whether the tunix package is already available. If it isn’t, the script silently installs the exact versions you need—ipywidgets, tensorboardX, transformers, grain, nest_asyncio, datasets, huggingface_hub, a recent numpy, tensorflow, and the latest JAX, Tunix, Qwix and Flax from source. It then removes any conflicting wandb or outdated flax installations. After the install finishes, it prints a clear message telling you to restart the runtime and rerun the cell.
Once the environment is ready, the next cell securely loads your Hugging Face token. It first looks for an HF_TOKEN environment variable, then tries to pull it from Colab’s secret store, and finally falls back to a prompt if neither is set. The token is stored back into the environment so downstream calls to login() work without extra code.
The script then disables wandb and tokenizer parallelism, silences TensorFlow logs, and forces TensorFlow to ignore GPUs so JAX can manage them cleanly. It prints the JAX backend and device list, and warns you if a GPU is present but JAX still sees only CPU—suggesting the exact command to reinstall JAX with CUDA support and restart.
With the environment verified, you can immediately define your model hyper‑parameters (rank, alpha, sequence lengths, learning rate, etc.), create the JAX mesh for FSDP/TP sharding, and instantiate the GRPO learner. No further fiddling with paths or version mismatches is required; everything points to the prepared checkpoint and TensorBoard directories.
Follow these two cells, restart when prompted, and you’ll be ready to start training Gemma‑3 with GRPO in a clean, reproducible setup—no more guesswork, no broken installs, just a working pipeline.
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