> For the complete documentation index, see [llms.txt](https://stackpi-intelligent.gitbook.io/stackpi-intelligent/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://stackpi-intelligent.gitbook.io/stackpi-intelligent/alpha-codium/usage/solving-the-entire-dataset.md).

# Solving the entire dataset

To solve the entire dataset, run:

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```
python -m alpha_codium.solve_dataset \
--dataset_name /path/to/dataset \
--split_name test
--database_solution_path /path/to/output/dir/dataset_output.json
```

* **Parameters:**
  * `split_name`: Could be either `valid` or `test`.
  * `database_solution_path`: Path to the directory where solutions will be saved
  * The `dataset` section in the configuration file contains the configuration for the running and evaluation of a dataset.

`dataset.num_iterations` defines the number of iterations for each problem (pass\@K). For a large number of iterations, it is recommended to introduce some randomness and different options for each iteration to achieve top results.

**Important Note:** Solving the entire dataset is a long process, and it may take a few days to complete with large models (e.g. GPT-4) and several iterations per problem.