fix: updated ways of getting obtaining logits_scaling

Signed-off-by: omobayode.fagbohungbe <[email protected]>

Author: bayo-ibm

fms_mo/utils/eval_utils.py

@@ -98,6 +98,7 @@ def eval_llm_1GPU(qcfg, model, test_dataset, pre_cache_func=None, **kwargs):  #
     logger.info("All blocks are computed for evaluation")
 
     nlls = []
+    logits_scaling = getattr(model.config, "logits_scaling", 1)
     # for i, data_mb in enumerate(dloader): #if using dloader.
     for i in tqdm(range(qcfg["n_samples"]), desc="Final Evaluating..."):
         hidden_states = qcfg["cached_input"][i].to(dev)
@@ -106,9 +107,7 @@ def eval_llm_1GPU(qcfg, model, test_dataset, pre_cache_func=None, **kwargs):  #
             hidden_states = ln_f(hidden_states)
         lm_head.to(dev)
         lm_logits = lm_head(hidden_states)
-
-        if model.config.model_type == "granite":
-            lm_logits /= model.config.logits_scaling
+        lm_logits /= logits_scaling
 
         # Shift so that tokens < n predict n
         shift_logits = lm_logits[:, :-1, :].contiguous().float()