  In this work, we focus on the global solvability and uniform large deviations
for the solutions of stochastic generalized Burgers-Huxley (SGBH) equation
perturbed by a small multiplicative white in time and colored in space noise.
The SGBH equation has the nonlinearity of polynomial order and noise considered
in this work is infinite dimensional with a coefficient having linear growth.
First, we prove the existence of a \textsl{unique local mild solution} in the
sense of Walsh to SGBH equation with the help of a truncation argument and
contraction mapping principle. Then the global solvability results are
established by using uniform bounds of the local mild solution, stopping time
arguments, tightness properties and Skorokhod's representation theorem.
  By using the uniform Laplace principle, we obtain the \textsl{large deviation
principle} (LDP) for the law of solutions to SGBH equation by using variational
representation methods. Further, we derive the \textsl{uniform large deviation
principle} (ULDP) for the law of solutions in two different topologies by using
a weak convergence method. First, in the $\mathrm{C}([0, T
];\mathrm{L}^p([0,1])) $ topology where the uniformity is over
$\mathrm{L}^p([0,1])$-bounded sets of initial conditions, and secondly in the
$\mathrm{C} ([0, T ] \times[0,1])$ topology with uniformity being over bounded
subsets in the $\mathrm{C}([0,1])$-norm.
  Finally, we consider SGBH equation perturbed by a space-time white noise with
bounded noise coefficient and establish the ULDP for the laws of solutions. The
results obtained in this work hold true for stochastic Burgers' as well as
Burgers-Huxley equations.
