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4 changes: 2 additions & 2 deletions gdf/readme.md
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Expand Up @@ -5,7 +5,7 @@ GDF is a simple framework for working with diffusion models. It implements most
, EDM, Rectified Flows, etc.) and makes it very easy to switch between them or combine different parts of different
frameworks

Using GDF is very straighforward, first of all just define an instance of the GDF class:
Using GDF is very straightforward, first of all just define an instance of the GDF class:

```python
from gdf import GDF
Expand Down Expand Up @@ -45,7 +45,7 @@ So it's very easy to extend this framework with custom schedulers, scalers, targ

When you define your training loop you can get all you need by just doing:
```python
shift, loss_shift = 1, 1 # this can be set to higher values as per what the Simple Diffusion paper sugested for high resolution
shift, loss_shift = 1, 1 # this can be set to higher values as per what the Simple Diffusion paper suggested for high resolution
for inputs, extra_conditions in dataloader_iterator:
noised, noise, target, logSNR, noise_cond, loss_weight = gdf.diffuse(inputs, shift=shift, loss_shift=loss_shift)
pred = diffusion_model(noised, noise_cond, extra_conditions)
Expand Down