Fix Marian model conversion (#30173)

* fix marian model coversion

* uncomment that line

* remove unnecessary code

* revert tie_weights, doesn't hurt

src/transformers/models/marian/convert_marian_tatoeba_to_pytorch.py

@@ -34,7 +34,6 @@
 
 DEFAULT_REPO = "Tatoeba-Challenge"
 DEFAULT_MODEL_DIR = os.path.join(DEFAULT_REPO, "models")
-LANG_CODE_URL = "https://datahub.io/core/language-codes/r/language-codes-3b2.csv"
 ISO_URL = "https://cdn-datasets.huggingface.co/language_codes/iso-639-3.csv"
 ISO_PATH = "lang_code_data/iso-639-3.csv"
 LANG_CODE_PATH = "lang_code_data/language-codes-3b2.csv"
@@ -277,13 +276,17 @@ def write_model_card(self, model_dict, dry_run=False) -> str:
             json.dump(metadata, writeobj)
 
     def download_lang_info(self):
+        global LANG_CODE_PATH
         Path(LANG_CODE_PATH).parent.mkdir(exist_ok=True)
         import wget
+        from huggingface_hub import hf_hub_download
 
         if not os.path.exists(ISO_PATH):
             wget.download(ISO_URL, ISO_PATH)
         if not os.path.exists(LANG_CODE_PATH):
-            wget.download(LANG_CODE_URL, LANG_CODE_PATH)
+            LANG_CODE_PATH = hf_hub_download(
+                repo_id="huggingface/language_codes_marianMT", filename="language-codes-3b2.csv", repo_type="dataset"
+            )
 
     def parse_metadata(self, model_name, repo_path=DEFAULT_MODEL_DIR, method="best"):
         p = Path(repo_path) / model_name

src/transformers/models/marian/convert_marian_to_pytorch.py

@@ -622,6 +622,10 @@ def load_marian_model(self) -> MarianMTModel:
             bias_tensor = nn.Parameter(torch.FloatTensor(self.final_bias))
             model.model.decoder.embed_tokens.weight = decoder_wemb_tensor
 
+        # handle tied embeddings, otherwise "from_pretrained" loads them incorrectly
+        if self.cfg["tied-embeddings"]:
+            model.lm_head.weight.data = model.model.decoder.embed_tokens.weight.data.clone()
+
         model.final_logits_bias = bias_tensor
 
         if "Wpos" in state_dict: