diff --git a/.gitignore b/.gitignore
index 4342412..e9c51ba 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,4 +1,5 @@
 __pycache__/
+tmp*
 *pyc
 /test/
 uno.out
diff --git a/README.md b/README.md
index c7d562d..cb23991 100644
--- a/README.md
+++ b/README.md
@@ -4,6 +4,7 @@
 [![pypi version](https://img.shields.io/pypi/v/pyAutoMR.svg)](https://pypi.python.org/pypi/pyAutoMR)
 [![Downloads](https://pepy.tech/badge/pyAutoMR/month)](https://pepy.tech/project/pyAutoMR)
 [![PyPI Downloads](https://img.shields.io/pypi/dm/pyAutoMR.svg?label=PyPI%20downloads)](https://pypi.org/project/pyAutoMR/)
+![GitHub Downloads][gh-downloads]
 
 The method used by this program is quite similar to [MOKIT](https://gitlab.com/jxzou/mokit). However, we try to do everything with PySCF and without Gaussian.
 
@@ -73,3 +74,11 @@ and cite every program called by pyAutoMR, such as PySCF, MOKIT, mrh, etc.
 
 If you peform calculations involving GVB, please also cite the following two papers
 > DOI: 10.1021/acs.jctc.8b00854; DOI: 10.1021/acs.jpca.0c05216.
+
+
+[![Ko-Fi][kofi-badge]][kofi]
+
+
+[gh-downloads]: https://img.shields.io/github/downloads/hebrewsnabla/pyAutoMR/total?color=pink&label=GitHub%20Downloads
+[kofi-badge]: https://img.shields.io/badge/Ko--fi-Buy%20me%20a%20coffee!-%2346b798.svg
+[kofi]: https://ko-fi.com/srwang
diff --git a/examples/tutorial/04-flipspin.py b/examples/tutorial/04-flipspin.py
new file mode 100644
index 0000000..e27dee1
--- /dev/null
+++ b/examples/tutorial/04-flipspin.py
@@ -0,0 +1,24 @@
+from automr import guess
+from pyscf import scf, fci, lib
+import numpy
+
+lib.num_threads(4)
+
+bl = 2.0
+theta = 104.52 * numpy.pi / 180.0 / 2.0
+z_coord = bl * numpy.cos(theta)
+y_coord = bl * numpy.sin(theta)
+
+atoms = f"O 0.00000000    0.00000000    0.00000000\n"
+atoms += f"H 0.00000000  {y_coord: 12.8f}  {z_coord: 12.8f}\n"
+atoms += f"H 0.00000000  {-y_coord: 12.8f}  {z_coord: 12.8f}\n"
+
+bas = 'sto-3g'
+
+#mf = guess.mix(atoms, bas, conv='tight', level_shift=0.2)
+mf = guess.flipspin(atoms, bas, 4, 'site', site=[0]) 
+mf.analyze()
+
+rhf = scf.RHF(mf.mol).run()
+full = fci.FCI(rhf).run()
+print(full.e_tot)