Turing.jl is not working

General Usage
2

Works fine for me on Julia 1.10.2 and Turing 0.30.7 (output below)

Output 
julia> @model function gdemo(x, y)
           s² ~ InverseGamma(2, 3)
               m ~ Normal(0, sqrt(s²))
                   x ~ Normal(m, sqrt(s²))
                       y ~ Normal(m, sqrt(s²))
                       end
gdemo (generic function with 2 methods)

julia>

julia> c6 = sample(gdemo(1.5, 2), NUTS(0.65), 1000)
┌ Info: Found initial step size
└   ϵ = 0.8
Sampling 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| Time: 0:00:03
Chains MCMC chain (1000×14×1 Array{Float64, 3}):

Iterations        = 501:1:1500
Number of chains  = 1
Samples per chain = 1000
Wall duration     = 3.47 seconds
Compute duration  = 3.47 seconds
parameters        = s², m
internals         = lp, n_steps, is_accept, acceptance_rate, log_density, hamiltonian_energy, hamiltonian_energy_error, max_hamiltonian_energy_error, tree_depth, numerical_error, step_size, nom_step_size

Summary Statistics
  parameters      mean       std      mcse   ess_bulk   ess_tail      rhat   ess_per_sec
      Symbol   Float64   Float64   Float64    Float64    Float64   Float64       Float64

          s²    2.0410    1.7763    0.0807   526.1108   574.8890    1.0012      151.4424
           m    1.2093    0.8292    0.0354   542.7964   642.2759    1.0054      156.2454

Quantiles
  parameters      2.5%     25.0%     50.0%     75.0%     97.5%
      Symbol   Float64   Float64   Float64   Float64   Float64

          s²    0.5958    1.0692    1.5760    2.4660    5.6401
           m   -0.3197    0.6868    1.1924    1.6953    2.8859