[Testing] Use a slightly larger model that works with group_size 128 (#1502)

SUMMARY:
- The previous model was too small for group_size 128; update to use a
larger one
- The point of the test is to validate the preset schemes (which include
128 as the group_size) so chose to update the model instead of the
recipe

Author: dsikka

tests/llmcompressor/transformers/gptq/test_oneshot.py

@@ -65,7 +65,7 @@ def setUp(self):
         import torch
 
         self.output = "./oneshot_output"
-        self.model = "roneneldan/TinyStories-1M"
+        self.model = "Xenova/llama2.c-stories110M"
         self.dataset = "open_platypus"
         self.device = "cuda:0" if torch.cuda.is_available() else "cpu"
 
@@ -106,7 +106,7 @@ def test_oneshot_application(self):
         assert weight_args.num_bits == 4
 
         # Check a specific layer is quantized
-        targetted_linear_layer = model_loaded.transformer.h[0].attn.attention.k_proj
+        targetted_linear_layer = model_loaded.model.layers[0].self_attn.k_proj
         assert hasattr(targetted_linear_layer, "quantization_scheme")
 
         # Check lm-head is not quantized