Create local Transformers Engine (#33218)

* Create local Transformers Engine

docs/source/en/main_classes/agent.md

@@ -87,12 +87,33 @@ These engines have the following specification:
 1. Follow the [messages format](../chat_templating.md) for its input (`List[Dict[str, str]]`) and return a string.
 2. Stop generating outputs *before* the sequences passed in the argument `stop_sequences`
 
-### HfEngine
+### TransformersEngine
 
-For convenience, we have added a `HfEngine` that implements the points above and uses an inference endpoint for the execution of the LLM.
+For convenience, we have added a `TransformersEngine` that implements the points above, taking a pre-initialized `Pipeline` as input.
 
 ```python
->>> from transformers import HfEngine
+>>> from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, TransformersEngine
+
+>>> model_name = "HuggingFaceTB/SmolLM-135M-Instruct"
+>>> tokenizer = AutoTokenizer.from_pretrained(model_name)
+>>> model = AutoModelForCausalLM.from_pretrained(model_name)
+
+>>> pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+>>> engine = TransformersEngine(pipe)
+>>> engine([{"role": "user", "content": "Ok!"}], stop_sequences=["great"])
+
+"What a "
+```
+
+[[autodoc]] TransformersEngine
+
+### HfApiEngine
+
+The `HfApiEngine` is an engine that wraps an [HF Inference API](https://huggingface.co/docs/api-inference/index) client for the execution of the LLM.
+
+```python
+>>> from transformers import HfApiEngine
 
 >>> messages = [
 ...   {"role": "user", "content": "Hello, how are you?"},
@@ -100,12 +121,12 @@ For convenience, we have added a `HfEngine` that implements the points above and
 ...   {"role": "user", "content": "No need to help, take it easy."},
 ... ]
 
->>> HfEngine()(messages, stop_sequences=["conversation"])
+>>> HfApiEngine()(messages, stop_sequences=["conversation"])
 
 "That's very kind of you to say! It's always nice to have a relaxed "
 ```
 
-[[autodoc]] HfEngine
+[[autodoc]] HfApiEngine
 
 
 ## Agent Types