[New Model]: jinaai/jina-reranker-v2-base-multilingual (#15876)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
Co-authored-by: DarkLight1337 <tlleungac@connect.ust.hk>

vllm/model_executor/models/roberta.py

@@ -13,7 +13,7 @@ from vllm.model_executor.layers.vocab_parallel_embedding import (
     VocabParallelEmbedding)
 from vllm.model_executor.model_loader.weight_utils import default_weight_loader
 from vllm.model_executor.models.bert import BertEmbeddingModel, BertModel
-from vllm.model_executor.models.utils import maybe_prefix
+from vllm.model_executor.models.utils import WeightsMapper, maybe_prefix
 from vllm.model_executor.pooling_metadata import PoolingMetadata
 from vllm.sequence import IntermediateTensors, PoolerOutput
 from vllm.transformers_utils.config import (
@@ -203,6 +203,18 @@ class RobertaForSequenceClassification(nn.Module, SupportsCrossEncoding,
        _pooler: An instance of Pooler used for pooling operations.
    """
 
+    jina_to_vllm_mapper = WeightsMapper(
+        orig_to_new_substr={
+            'emb_ln': "embeddings.LayerNorm",
+            'layers': "layer",
+            'mixer.Wqkv': "attention.self.qkv_proj",
+            'mixer.out_proj': "attention.output.dense",
+            'norm1': "attention.output.LayerNorm",
+            'mlp.fc1': "intermediate.dense",
+            'mlp.fc2': "output.dense",
+            'norm2': "output.LayerNorm",
+        })
+
     def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
         super().__init__()
         config = vllm_config.model_config.hf_config
@@ -219,8 +231,9 @@ class RobertaForSequenceClassification(nn.Module, SupportsCrossEncoding,
         self._pooler = CrossEncodingPooler(config, self.classifier)
 
     def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
-
         bert_weights, task_weights = roberta_task_weights_filter(weights)
+        bert_weights = self.jina_to_vllm_mapper.apply(bert_weights)
+
         self.roberta.load_weights(bert_weights)
 
         params_dict = dict(self.named_parameters())