Update README [no ci]

README.md

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 # QiskitOpt.jl
-JuMP wrapper for IBMQ Optimization Algorithms (ft Anneal.jl)
+IBM Qiskit Optimization Wrapper for JuMP (ft. [Anneal.jl](https://github.com/psrenergy/Anneal.jl))
+
+## Installation
+```julia
+julia> import Pkg
+
+julia> Pkg.add(url="https://github.com/psrenergy/QiskitOpt.jl")
+```
+
+## Basic Usage
+```julia
+using JuMP
+using QistkitOpt
+
+# Using QAOA
+model = Model(QiskitOpt.QAOA.Optimizer)
+
+# Using VQE
+model = Model(QiskitOpt.VQE.Optimizer)
+
+Q = [
+   -1  2  2
+    2 -1  2
+    2  2 -1
+]
+
+@variable(model, x[1:3], Bin)
+@objective(model, Min, x' * Q * x)
+
+optimize!(model)
+
+for i = 1:result_count(model)
+    xi = value.(x; result=i)
+    yi = objective_value(model; result=i)
+
+    println("f($xi) = $yi")
+end
+```
+
+## API Token
+To access IBM's Quantum Computers, it is necessary to create an account at [IBM Q](https://quantum-computing.ibm.com/) to obtain an API Token and run the following python code:
+
+```python
+from qiskit import IBMQ
+
+IBMQ.save_account("YOUR_TOKEN_HERE")
+```
+
+Another option is to set the `IBMQ_API_TOKEN` environment variable before loading `QAOA.jl`:
+```shell
+$ export IBQM_API_TOKEN=YOUR_TOKEN_HERE
+
+$ julia
+
+julia> using QAOA
+```
+
+**Disclaimer:** _The IBM Qiskit Optimization Wrapper for Julia is not officially supported by IBM. If you are a commercial customer interested in official support for Julia from IBM, let them know!_
+
+**Note**: _If you are using [QAOA.jl](https://github.com/psrenergy/QiskitOpt.jl) in your project, we recommend you to include the `.CondaPkg` entry in your `.gitignore` file. The PythonCall module will place a lot of files in this folder when building its Python environment._
+