Here’s a related issue:

```
startch = sample(model,
MH(diagm([.002 for i in 1:npars])),1200; thinning=10, init_theta=op.values.array)
resumech = sample(model,MH(diagm([.002 for i in 1:npars])),1200;resume_from=startch)
```

The second line gives an error:

```
julia> resumech = sample(model,MH(diagm([.002 for i in 1:npars])),1200;resume_from=startch)
ERROR: type NamedTuple has no field model
Stacktrace:
[1] getindex(t::NamedTuple{(:start_time, :stop_time), Tuple{Float64, Float64}}, i::Symbol)
@ Base ./namedtuple.jl:127
[2] resume(rng::Random._GLOBAL_RNG, chain::Chains{Float64, AxisArrays.AxisArray{Float64, 3, Array{Float64, 3}, Tuple{AxisArrays.Axis{:iter, StepRange{Int64, Int64}}, AxisArrays.Axis{:var, Vector{Symbol}}, AxisArrays.Axis{:chain, UnitRange{Int64}}}}, Missing, NamedTuple{(:parameters, :internals), Tuple{Vector{Symbol}, Vector{Symbol}}}, NamedTuple{(:start_time, :stop_time), Tuple{Float64, Float64}}}, args::Int64; progress::Bool, kwargs::Base.Pairs{Symbol, UnionAll, Tuple{Symbol}, NamedTuple{(:chain_type,), Tuple{UnionAll}}})
@ Turing.Inference ~/.julia/packages/Turing/uMQmD/src/inference/Inference.jl:404
[3] resume(chain::Chains{Float64, AxisArrays.AxisArray{Float64, 3, Array{Float64, 3}, Tuple{AxisArrays.Axis{:iter, StepRange{Int64, Int64}}, AxisArrays.Axis{:var, Vector{Symbol}}, AxisArrays.Axis{:chain, UnitRange{Int64}}}}, Missing, NamedTuple{(:parameters, :internals), Tuple{Vector{Symbol}, Vector{Symbol}}}, NamedTuple{(:start_time, :stop_time), Tuple{Float64, Float64}}}, args::Int64; kwargs::Base.Pairs{Symbol, Any, Tuple{Symbol, Symbol}, NamedTuple{(:chain_type, :progress), Tuple{UnionAll, Bool}}})
@ Turing.Inference ~/.julia/packages/Turing/uMQmD/src/inference/Inference.jl:396
[4] sample(rng::Random._GLOBAL_RNG, model::DynamicPPL.Model{typeof(teamskill), (:Nteams, :orefteam, :drefteam, :m1, :m2, :m3, :m4, :week, :ns, :hometeam, :homepts, :awayteam, :awaypts), (), (), Tuple{Int64, Vector{Union{Nothing, Int64}}, Vector{Union{Nothing, Int64}}, Float64, Float64, Float64, Float64, Vector{Int64}, Vector{Bool}, Vector{Union{Nothing, Int64}}, Vector{Union{Missing, Int64}}, Vector{Union{Nothing, Int64}}, Vector{Union{Missing, Int64}}}, Tuple{}, DynamicPPL.DefaultContext}, sampler::DynamicPPL.Sampler{MH{(), RandomWalkProposal{false, ZeroMeanFullNormal{Tuple{Base.OneTo{Int64}}}}}}, N::Int64; chain_type::Type, resume_from::Chains{Float64, AxisArrays.AxisArray{Float64, 3, Array{Float64, 3}, Tuple{AxisArrays.Axis{:iter, StepRange{Int64, Int64}}, AxisArrays.Axis{:var, Vector{Symbol}}, AxisArrays.Axis{:chain, UnitRange{Int64}}}}, Missing, NamedTuple{(:parameters, :internals), Tuple{Vector{Symbol}, Vector{Symbol}}}, NamedTuple{(:start_time, :stop_time), Tuple{Float64, Float64}}}, progress::Bool, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ Turing.Inference ~/.julia/packages/Turing/uMQmD/src/inference/Inference.jl:159
[5] sample(rng::Random._GLOBAL_RNG, model::DynamicPPL.Model{typeof(teamskill), (:Nteams, :orefteam, :drefteam, :m1, :m2, :m3, :m4, :week, :ns, :hometeam, :homepts, :awayteam, :awaypts), (), (), Tuple{Int64, Vector{Union{Nothing, Int64}}, Vector{Union{Nothing, Int64}}, Float64, Float64, Float64, Float64, Vector{Int64}, Vector{Bool}, Vector{Union{Nothing, Int64}}, Vector{Union{Missing, Int64}}, Vector{Union{Nothing, Int64}}, Vector{Union{Missing, Int64}}}, Tuple{}, DynamicPPL.DefaultContext}, alg::MH{(), RandomWalkProposal{false, ZeroMeanFullNormal{Tuple{Base.OneTo{Int64}}}}}, N::Int64; kwargs::Base.Pairs{Symbol, Chains{Float64, AxisArrays.AxisArray{Float64, 3, Array{Float64, 3}, Tuple{AxisArrays.Axis{:iter, StepRange{Int64, Int64}}, AxisArrays.Axis{:var, Vector{Symbol}}, AxisArrays.Axis{:chain, UnitRange{Int64}}}}, Missing, NamedTuple{(:parameters, :internals), Tuple{Vector{Symbol}, Vector{Symbol}}}, NamedTuple{(:start_time, :stop_time), Tuple{Float64, Float64}}}, Tuple{Symbol}, NamedTuple{(:resume_from,), Tuple{Chains{Float64, AxisArrays.AxisArray{Float64, 3, Array{Float64, 3}, Tuple{AxisArrays.Axis{:iter, StepRange{Int64, Int64}}, AxisArrays.Axis{:var, Vector{Symbol}}, AxisArrays.Axis{:chain, UnitRange{Int64}}}}, Missing, NamedTuple{(:parameters, :internals), Tuple{Vector{Symbol}, Vector{Symbol}}}, NamedTuple{(:start_time, :stop_time), Tuple{Float64, Float64}}}}}})
@ Turing.Inference ~/.julia/packages/Turing/uMQmD/src/inference/Inference.jl:142
[6] sample(model::DynamicPPL.Model{typeof(teamskill), (:Nteams, :orefteam, :drefteam, :m1, :m2, :m3, :m4, :week, :ns, :hometeam, :homepts, :awayteam, :awaypts), (), (), Tuple{Int64, Vector{Union{Nothing, Int64}}, Vector{Union{Nothing, Int64}}, Float64, Float64, Float64, Float64, Vector{Int64}, Vector{Bool}, Vector{Union{Nothing, Int64}}, Vector{Union{Missing, Int64}}, Vector{Union{Nothing, Int64}}, Vector{Union{Missing, Int64}}}, Tuple{}, DynamicPPL.DefaultContext}, alg::MH{(), RandomWalkProposal{false, ZeroMeanFullNormal{Tuple{Base.OneTo{Int64}}}}}, N::Int64; kwargs::Base.Pairs{Symbol, Chains{Float64, AxisArrays.AxisArray{Float64, 3, Array{Float64, 3}, Tuple{AxisArrays.Axis{:iter, StepRange{Int64, Int64}}, AxisArrays.Axis{:var, Vector{Symbol}}, AxisArrays.Axis{:chain, UnitRange{Int64}}}}, Missing, NamedTuple{(:parameters, :internals), Tuple{Vector{Symbol}, Vector{Symbol}}}, NamedTuple{(:start_time, :stop_time), Tuple{Float64, Float64}}}, Tuple{Symbol}, NamedTuple{(:resume_from,), Tuple{Chains{Float64, AxisArrays.AxisArray{Float64, 3, Array{Float64, 3}, Tuple{AxisArrays.Axis{:iter, StepRange{Int64, Int64}}, AxisArrays.Axis{:var, Vector{Symbol}}, AxisArrays.Axis{:chain, UnitRange{Int64}}}}, Missing, NamedTuple{(:parameters, :internals), Tuple{Vector{Symbol}, Vector{Symbol}}}, NamedTuple{(:start_time, :stop_time), Tuple{Float64, Float64}}}}}})
```