A Dirichlet $k$-partition of a domain $U \subseteq \mathbb{R}^d$ is a collection of $k$ pairwise disjoint open subsets such that the sum of their first Laplace-Dirichlet eigenvalues is minimal. A discrete version of Dirichlet partitions has been posed on graphs with applications in data analysis. Both versions admit variational formulations: solutions are characterized by minimizers of the Dirichlet energy of mappings from $U$ into a singular space $Σ_k \subseteq \mathbb{R}^k$. In this paper, we extend results of N.\ García Trillos and D.\ Slepčev to show that there exist solutions of the continuum problem arising as limits to solutions of a sequence of discrete problems. Specifically, a sequence of points $\{x_i\}_{i \in \mathbb{N}}$ from $U$ is sampled i.i.d.\ with respect to a given probability measure $ν$ on $U$ and for all $n \in \mathbb{N}$, a geometric graph $G_n$ is constructed from the first $n$ points $x_1, x_2, \ldots, x_n$ and the pairwise distances between the points. With probability one with respect to the choice of points $\{x_i\}_{i \in \mathbb{N}}$, we show that as $n \to \infty$ the discrete Dirichlet energies for functions $G_n \to Σ_k$ $Γ$-converge to (a scalar multiple of) the continuum Dirichlet energy for functions $U \to Σ_k$ with respect to a metric coming from the theory of optimal transport. This, along with a compactness property for the aforementioned energies that we prove, implies the convergence of minimizers. When $ν$ is the uniform distribution, our results also imply the statistical consistency statement that Dirichlet partitions of geometric graphs converge to partitions of the sampled space in the Hausdorff sense.