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@@ -34,39 +34,9 @@ documentation/pymf.md
 
 ## What is pymf?
 
-Pymf is a Python package for finding mean-field corrections to the non-interacting part of a Hamiltonian. It is designed to be simple to use and flexible enough to handle a wide range of systems. Pymf works by solving the mean-field equations self-consistently.
-
-Finding a mean-field solution is a 4-step process:
-
-- Define the non-interacting and interacting part of the Hamiltonian separately as hopping dictionaries.
-- Combine the non-interacting and interacting parts togher with your filling into a `Model` object.
-- Provide a starting guess and the number of k-points to use the `solver` function and find the mean-field correction.
-- Add the mean-field correction to the non-interacting part to calculate the total Hamiltonian.
-
-```python
-import pymf
-
-model = pymf.Model(h_0, h_int, filling=filling)
-mf_sol = pymf.solver(model, guess, nk=nk)
-h_full = pymf.add_tb(h_0, mf_sol)
-```
 
 ## Why pymf?
 
-Here is why you should use pymf:
-
-* Minimal
-
-  Pymf contains the minimum of what you need to solve mean-field equations.
-
-* Simple
-
-  The workflow is simple and straightforward.
-
-* Time-effective
-
-  As pymf uses tight-binding dictionaries as input and returns, you can calculate the mean-field corrections on a coarse grid, but use the full Hamiltonian on a fine grid for observables afterward.
-
 
 ## How does pymf work?