diff --git a/src/transformers/convert_marian_to_pytorch.py b/src/transformers/convert_marian_to_pytorch.py
index ce001166a85..6135f61275c 100644
--- a/src/transformers/convert_marian_to_pytorch.py
+++ b/src/transformers/convert_marian_to_pytorch.py
@@ -40,33 +40,7 @@ def check_if_models_are_dominated(old_repo_path="OPUS-MT-train/models", new_repo
     """Make a blacklist for models where we have already ported the same language pair, and the ported model has higher BLEU score."""
     import pandas as pd
 
-    released_cols = [
-        "url_base",
-        "pair",  # (ISO639-3/ISO639-5 codes),
-        "short_pair",  # (reduced codes),
-        "chrF2_score",
-        "bleu",
-        "brevity_penalty",
-        "ref_len",
-        "src_name",
-        "tgt_name",
-    ]
-
-    released = pd.read_csv(f"{new_repo_path}/released-models.txt", sep="\t", header=None).iloc[:-1]
-    released.columns = released_cols
-    old_reg = make_registry(repo_path=old_repo_path)
-    old_reg = pd.DataFrame(old_reg, columns=["id", "prepro", "url_model", "url_test_set"])
-    assert old_reg.id.value_counts().max() == 1
-    old_reg = old_reg.set_index("id")
-
-    released["fname"] = released["url_base"].apply(
-        lambda x: remove_suffix(remove_prefix(x, "https://object.pouta.csc.fi/Tatoeba-Challenge/opus"), ".zip")
-    )
-
-    released["2m"] = released.fname.str.startswith("2m")
-    released["date"] = pd.to_datetime(released["fname"].apply(lambda x: remove_prefix(remove_prefix(x, "2m-"), "-")))
-
-    newest_released = released.dsort("date").drop_duplicates(["short_pair"], keep="first")
+    newest_released, old_reg, released = get_released_df(new_repo_path, old_repo_path)
 
     short_to_new_bleu = newest_released.set_index("short_pair").bleu
 
@@ -94,8 +68,38 @@ def check_if_models_are_dominated(old_repo_path="OPUS-MT-train/models", new_repo
     ).fillna(-1)
 
     dominated = cmp_df[cmp_df.old_bleu > cmp_df.new_bleu]
+    whitelist_df = cmp_df[cmp_df.old_bleu <= cmp_df.new_bleu]
     blacklist = dominated.long.unique().tolist()  # 3 letter codes
-    return dominated, blacklist
+    return whitelist_df, dominated, blacklist
+
+
+def get_released_df(new_repo_path, old_repo_path):
+    import pandas as pd
+
+    released_cols = [
+        "url_base",
+        "pair",  # (ISO639-3/ISO639-5 codes),
+        "short_pair",  # (reduced codes),
+        "chrF2_score",
+        "bleu",
+        "brevity_penalty",
+        "ref_len",
+        "src_name",
+        "tgt_name",
+    ]
+    released = pd.read_csv(f"{new_repo_path}/released-models.txt", sep="\t", header=None).iloc[:-1]
+    released.columns = released_cols
+    old_reg = make_registry(repo_path=old_repo_path)
+    old_reg = pd.DataFrame(old_reg, columns=["id", "prepro", "url_model", "url_test_set"])
+    assert old_reg.id.value_counts().max() == 1
+    old_reg = old_reg.set_index("id")
+    released["fname"] = released["url_base"].apply(
+        lambda x: remove_suffix(remove_prefix(x, "https://object.pouta.csc.fi/Tatoeba-Challenge/opus"), ".zip")
+    )
+    released["2m"] = released.fname.str.startswith("2m")
+    released["date"] = pd.to_datetime(released["fname"].apply(lambda x: remove_prefix(remove_prefix(x, "2m-"), "-")))
+    newest_released = released.dsort("date").drop_duplicates(["short_pair"], keep="first")
+    return newest_released, old_reg, released
 
 
 def remove_prefix(text: str, prefix: str):
@@ -323,6 +327,44 @@ def get_clean_model_id_mapping(multiling_model_ids):
     return {x: convert_opus_name_to_hf_name(x) for x in multiling_model_ids}
 
 
+def expand_group_to_two_letter_codes(grp_name):
+    raise NotImplementedError()
+
+
+def get_two_letter_code(three_letter_code):
+    raise NotImplementedError()
+    # return two_letter_code
+
+
+def get_tags(code, ref_name):
+    if len(code) == 2:
+        assert "languages" not in ref_name, f"{code}: {ref_name}"
+        return [code], False
+    elif "languages" in ref_name:
+        group = expand_group_to_two_letter_codes(code)
+        group.append(code)
+        return group, True
+    else:  # zho-> zh
+        raise ValueError(f"Three letter monolingual code: {code}")
+
+
+def resolve_lang_code(r):
+    """R is a row in ported"""
+    short_pair = r.short_pair
+    src, tgt = short_pair.split("-")
+    src_tags, src_multilingual = get_tags(src, r.src_name)
+    assert isinstance(src_tags, list)
+    tgt_tags, tgt_multilingual = get_tags(src, r.tgt_name)
+    assert isinstance(tgt_tags, list)
+    if src_multilingual:
+        src_tags.append("multilingual_src")
+    if tgt_multilingual:
+        tgt_tags.append("multilingual_tgt")
+    return src_tags + tgt_tags
+
+    # process target
+
+
 def make_registry(repo_path="Opus-MT-train/models"):
     if not (Path(repo_path) / "fr-en" / "README.md").exists():
         raise ValueError(
@@ -666,6 +708,7 @@ def convert(source_dir: Path, dest_dir):
     # ^^ Save human readable marian config for debugging
 
     model = opus_state.load_marian_model()
+    model = model.half()
     model.save_pretrained(dest_dir)
     model.from_pretrained(dest_dir)  # sanity check