expand documentation to offer two paths for weights

Signed-off-by: ❤️ <[email protected]>

docs/python.md

@@ -50,8 +50,22 @@ Prepare the model so multiple predictions run efficiently.
 
 Use this _optional_ method to include any expensive one-off operations in here like loading trained models, instantiate data transformations, etc.
 
-This method is also where you should download the weights for your model (e.g. using [`pget`](https://github.com/replicate/pget)). Storing your weights with your image directly can cause long `cog build` times and large images.
-> If this is not an option for you, you can use the `--separate-weights` flag on `cog build` to store weights in a [separate layer](https://github.com/replicate/cog/blob/12ac02091d93beebebed037f38a0c99cd8749806/docs/getting-started.md?plain=1#L219).
+Many models use this method to download their weights (e.g. using [`pget`](https://github.com/replicate/pget)). 
+
+This has some advantages:
+- Smaller image sizes
+- Faster build times
+- Faster pushes and inference on [Replicate](https://replicate.com)
+
+However, this may also significantly increase your `setup()` time.
+
+As an alternative, some choose to store their weights directly in the image. You can simply leave your weights in the directory alongside your `cog.yaml` and ensure they are not excluded in your `.dockerignore` file.
+
+While this will increase your image size and build time, it offers other advantages:
+- Faster `setup()` time
+- Ensures idempotency and reduces your model's reliance on external systems- Preserves reproducibility as your model will be self-contained in the image
+
+> When using this method, you should use the `--separate-weights` flag on `cog build` to store weights in a [separate layer](https://github.com/replicate/cog/blob/12ac02091d93beebebed037f38a0c99cd8749806/docs/getting-started.md?plain=1#L219).
 
 ### `Predictor.predict(**kwargs)`