Upload merge_ministral.py with huggingface_hub

merge_ministral.py

@@ -13,8 +13,7 @@ print("Base: mistralai/Ministral-3-14B-Base-2512")
 print("LoRA: RoleModel/ministral-14b-reasoning-merged")
 print("Output: RoleModel/ministral-14b-merged-official")
 
-print("
-[1/5] Loading base model...")
+print("[1/5] Loading base model...")
 base = AutoModelForCausalLM.from_pretrained(
     "mistralai/Ministral-3-14B-Base-2512",
     torch_dtype=torch.bfloat16,
@@ -23,29 +22,24 @@ base = AutoModelForCausalLM.from_pretrained(
 )
 print(f"Base model class: {base.__class__.__name__}")
 
-print("
-[2/5] Loading LoRA adapter...")
+print("[2/5] Loading LoRA adapter...")
 model = PeftModel.from_pretrained(base, "RoleModel/ministral-14b-reasoning-merged")
 print("LoRA adapter loaded")
 
-print("
-[3/5] Merging weights...")
+print("[3/5] Merging weights...")
 merged = model.merge_and_unload()
 print("Merge complete")
 
-print("
-[4/5] Saving merged model...")
+print("[4/5] Saving merged model...")
 merged.save_pretrained("./merged-model", safe_serialization=True)
 print("Model saved locally")
 
-print("
-[4b/5] Saving tokenizer...")
+print("[4b/5] Saving tokenizer...")
 tok = AutoTokenizer.from_pretrained("mistralai/Ministral-3-14B-Base-2512", trust_remote_code=True)
 tok.save_pretrained("./merged-model")
 print("Tokenizer saved")
 
-print("
-[5/5] Pushing to Hub...")
+print("[5/5] Pushing to Hub...")
 api = HfApi()
 api.create_repo("RoleModel/ministral-14b-merged-official", exist_ok=True, private=True, token=os.environ.get("HF_TOKEN"))
 api.upload_folder(
@@ -55,6 +49,5 @@ api.upload_folder(
     token=os.environ.get("HF_TOKEN")
 )
 
-print("
-=== DONE ===")
+print("=== DONE ===")
 print("Merged model: https://huggingface.co/RoleModel/ministral-14b-merged-official")