Update app.py

app.py

@@ -10,18 +10,27 @@ base_model_name = "facebook/nllb-200-distilled-600M"
 adapter_en_to_no = "entropy25/mt_en_no_oil"
 adapter_no_to_en = "entropy25/mt_no_en_oil"
 
-# 加载 tokenizer 和基础模型
+# 加载 tokenizer
 tokenizer = AutoTokenizer.from_pretrained(base_model_name)
-base_model = AutoModelForSeq2SeqLM.from_pretrained(
+
+# 方法1：为每个方向加载独立的基础模型
+print("Loading English to Norwegian model...")
+base_model_en_to_no = AutoModelForSeq2SeqLM.from_pretrained(
     base_model_name,
     torch_dtype=torch.float16,
     low_cpu_mem_usage=True,
     device_map="auto"
 )
+model_en_to_no = PeftModel.from_pretrained(base_model_en_to_no, adapter_en_to_no)
 
-# 加载两个方向的模型
-model_en_to_no = PeftModel.from_pretrained(base_model, adapter_en_to_no)
-model_no_to_en = PeftModel.from_pretrained(base_model, adapter_no_to_en)
+print("Loading Norwegian to English model...")
+base_model_no_to_en = AutoModelForSeq2SeqLM.from_pretrained(
+    base_model_name,
+    torch_dtype=torch.float16,
+    low_cpu_mem_usage=True,
+    device_map="auto"
+)
+model_no_to_en = PeftModel.from_pretrained(base_model_no_to_en, adapter_no_to_en)
 
 def translate(text, source_lang, target_lang):
     if not text.strip():