Pipeline: simple API for assisted generation (#34504)

Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

docs/source/en/generation_strategies.md

@@ -441,6 +441,28 @@ To enable assisted decoding, set the `assistant_model` argument with a model.
 ['Alice and Bob are sitting in a bar. Alice is drinking a beer and Bob is drinking a']
 ```
 
+<Tip>
+
+If you're using a `pipeline` object, all you need to do is to pass the assistant checkpoint under `assistant_model`
+
+```python
+>>> from transformers import pipeline
+>>> import torch
+
+>>> pipe = pipeline(
+...     "text-generation",
+...     model="meta-llama/Llama-3.1-8B",
+...     assistant_model="meta-llama/Llama-3.2-1B",  # This extra line is all that's needed, also works with UAD
+...     torch_dtype=torch.bfloat16
+>>> )
+>>> pipe_output = pipe("Once upon a time, ", max_new_tokens=50, do_sample=False)
+>>> pipe_output[0]["generated_text"]
+'Once upon a time, 3D printing was a niche technology that was only'
+```
+
+</Tip>
+
+
 When using assisted decoding with sampling methods, you can use the `temperature` argument to control the randomness,
 just like in multinomial sampling. However, in assisted decoding, reducing the temperature may help improve the latency.