Creating logistic growth model

I am trying to fit a logistic growth model fit to my data.
My data set is a two column series of years and number of birds.
Year. Number of birds
1900 800
1910 905
..... ....(An asymptote is eventually reached)

The data eventually reaches some carrying capacity and ends up become more stabilized in the base plot:

plot(Count~Year, data=Cormorants, type= "l")

I'm confused how I can fit a logistic growth model to the data to make an "S'" shaped curve.
Very similarly to how populations reach their carrying capacity.
I've tried creating a glm model with the code:
model<- glm(Count~Year, binomial)

but I get an error in eval (family$initialize) : y values must be 0<= y<=1

Am I going about this wrong?

Something like
nls(Count~b0 + b1*exp(b2*year)/exp(1+b2*year), start=list(b0=0,b1=1,b2=3))
although I'm sure that logistic formula isn't exactly what you want.

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Could you clarify what each of the b0,b1, and b2 are indicating?

Those are the parameters to be estimated.

Essentially, you specify a nonlinear functional form that can take the shape of an S-curve. nls() will estimate the parameters of that function.

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