feat: clean README

Author: Oisin-M

README.md

@@ -53,73 +53,9 @@ pip install gfn-layer
 ```
 **Note:** the package name on PyPI is **gfn-layer**, gfn refers to a different package.
 
-For a developer installation
-```
-git clone https://github.com/Oisin-M/gfn.git
-cd gfn
-pip install -e .
-pre-commit install
-```
-
 ## Quickstart
 
-Using `gfn` is intuitive - the `GFN` layer is an extension of the `torch.nn.Linear` layer. Simply import it with `from gfn import GFN` and use as follows:
-
-**No graph (equivalent to `torch.nn.Linear`)**
-```python
-gfn_layer = GFN(in_features=2, out_features=3)
-
-x = torch.ones(2)
-
-y = gfn_layer(x)
-assert y.shape[-1] == 3
-```
-
-**In graph only**
-```python
-# in graph with 2 nodes at (0, 0) and (1, 0)
-original_in_graph = torch.tensor([(0,0), (1,0)])
-gfn_layer = GFN(in_features=original_in_graph, out_features=3)
-
-# predict using graph of 4 nodes: (0.5, 0.5), (1.5, 1.5), (1,1) and (0, 0.5)
-new_in_graph = torch.tensor([(0.5, 0.5), (1.5, 1.5), (1, 1), (0, 0.5)])
-x = torch.ones(4)
-
-y = gfn_layer(x, in_graph=new_in_graph)
-assert y.shape[-1] == 3
-```
-
-**Out graph only**
-```python
-# out graph with 3 nodes at (0, 0), (-1, 0) and (0, -1)
-original_out_graph = torch.tensor([(0,0), (-1,0), [0,-1]])
-gfn_layer = GFN(in_features=2, out_features=original_out_graph)
-
-# predict at graph of 5 nodes: (-0.5, -0.5), (-1.5, -1.5), (-1, -1), (0, -0.5) and (-0.5, 0)
-new_out_graph = torch.tensor([(-0.5, -0.5), (-1.5, -1.5), (-1, -1), (0, -0.5), (-0.5, 0)])
-x = torch.ones(2)
-
-y = gfn_layer(x, out_graph=new_out_graph)
-assert y.shape[-1] == 5
-```
-
-**Both out graph and in graph**
-```python
-# in graph of 2 nodes
-original_in_graph = torch.tensor([(0,0), (1,0)])
-# out graph of 3 nodes
-original_out_graph = torch.tensor([(0,0), (-1,0), [0,-1]])
-gfn_layer = GFN(in_features=original_in_graph, out_features=original_out_graph)
-
-# predict using graph of 4 nodes
-new_in_graph = torch.tensor([(0.5, 0.5), (1.5, 1.5), (1, 1), (0, 0.5)])
-# predict at graph of 5 nodes
-new_out_graph = torch.tensor([(-0.5, -0.5), (-1.5, -1.5), (-1, -1), (0, -0.5), (-0.5, 0)])
-x = torch.ones(4)
-
-y = gfn_layer(x, out_graph=new_out_graph)
-assert y.shape[-1] == 5
-```
+See the [user guide](https://gfn-layer.readthedocs.io/en/latest/userguide.html) to get started!
 
 ## Citing
 If this work is useful to you, please cite