init

whisper/check_lora_weights.py

@@ -0,0 +1,14 @@
+from peft import PeftModel
+from transformers import WhisperForConditionalGeneration
+
+base = WhisperForConditionalGeneration.from_pretrained("openai/whisper-small")
+model = PeftModel.from_pretrained(base, "whisper-small/checkpoint-1000")
+
+# check if any lora weights are actually non-zero
+import torch
+for name, param in model.named_parameters():
+    if "lora" in name and param.abs().sum() > 0:
+        print(f"[+] active: {name} | sum: {param.abs().sum().item():.4f}")
+        break
+else:
+    print("[-] no active lora weights found")