review comments

Signed-off-by: Akihiko Kuroda <akihikokuroda2020@gmail.com>

Author: akihikokuroda

docs/examples/intrinsics/intrinsics.py

@@ -1,8 +1,5 @@
 # pytest: huggingface, requires_heavy_ram, llm
 
-import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
 import mellea.stdlib.functional as mfuncs
 from mellea.backends.adapters.adapter import AdapterType, IntrinsicAdapter
 from mellea.backends.huggingface import LocalHFBackend
@@ -12,14 +9,7 @@
 # This is an example for how you would directly use intrinsics. See `mellea/stdlib/intrinsics/rag.py`
 # for helper functions.
 
-# Force CPU usage by creating custom config
-model_id = "ibm-granite/granite-3.3-8b-instruct"
-device = torch.device("cpu")
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = AutoModelForCausalLM.from_pretrained(model_id, device_map="cpu")
-
-custom_config = (tokenizer, model, device)
-backend = LocalHFBackend(model_id=model_id, custom_config=custom_config)
+backend = LocalHFBackend(model_id="ibm-granite/granite-3.3-8b-instruct")
 
 # Create the Adapter. IntrinsicAdapter's default to ALORAs.
 req_adapter = IntrinsicAdapter(