Fix Falcon validation (openvinotoolkit#1664)

The issue is not reproduced if using optimum-cli for export but only
when cloning the entire model repo from the HF Hub.

Author: AlexKoff88

tools/who_what_benchmark/whowhatbench/model_loaders.py

@@ -19,7 +19,10 @@ def __init__(self, model, model_dir, model_type):
         self.model_type = model_type
 
         if model_type == "text" or model_type == "visual-text":
-            self.config = AutoConfig.from_pretrained(model_dir, trust_remote_code=True)
+            try:
+                self.config = AutoConfig.from_pretrained(model_dir, trust_remote_code=True)
+            except Exception:
+                self.config = AutoConfig.from_pretrained(model_dir)
         elif model_type == "text-to-image":
             self.config = DiffusionPipeline.load_config(
                 model_dir, trust_remote_code=True)
@@ -101,17 +104,27 @@ def load_text_model(
             model = OVModelForCausalLM.from_pretrained(
                 model_id, trust_remote_code=True, device=device, ov_config=ov_config
             )
-        except ValueError:
-            config = AutoConfig.from_pretrained(
-                model_id, trust_remote_code=True)
-            model = OVModelForCausalLM.from_pretrained(
-                model_id,
-                config=config,
-                trust_remote_code=True,
-                use_cache=True,
-                device=device,
-                ov_config=ov_config,
-            )
+        except Exception:
+            try:
+                config = AutoConfig.from_pretrained(
+                    model_id, trust_remote_code=True)
+                model = OVModelForCausalLM.from_pretrained(
+                    model_id,
+                    config=config,
+                    trust_remote_code=True,
+                    use_cache=True,
+                    device=device,
+                    ov_config=ov_config,
+                )
+            except Exception:
+                config = AutoConfig.from_pretrained(model_id)
+                model = OVModelForCausalLM.from_pretrained(
+                    model_id,
+                    config=config,
+                    use_cache=True,
+                    device=device,
+                    ov_config=ov_config,
+                )
 
     return model