chore: import upstream snapshot with attribution

2026-07-13 13:34:58 +08:00
commit a203934033
1368 changed files with 175001 additions and 0 deletions
@@ -0,0 +1,89 @@
+# Copyright (c) ModelScope Contributors. All rights reserved.
+import torch.nn.functional as F
+from transformers import AutoModel, AutoModelForSequenceClassification, PreTrainedModel
+
+from swift.template import TemplateType
+from swift.utils import get_logger
+from ..constant import BertModelType, LLMModelType
+from ..model_meta import Model, ModelGroup, ModelMeta
+from ..register import ModelLoader, register_model
+
+logger = get_logger()
+
+
+class ModernBertLoader(ModelLoader):
+
+    def get_model(self, model_dir: str, config, *args, **kwargs) -> PreTrainedModel:
+        config.reference_compile = False
+        return super().get_model(model_dir, config, *args, **kwargs)
+
+
+register_model(
+    ModelMeta(
+        BertModelType.modern_bert, [
+            ModelGroup([
+                Model('answerdotai/ModernBERT-base', 'answerdotai/ModernBERT-base'),
+                Model('answerdotai/ModernBERT-large', 'answerdotai/ModernBERT-large'),
+            ])
+        ],
+        ModernBertLoader,
+        template=TemplateType.dummy,
+        requires=['transformers>=4.48'],
+        architectures=['ModernBertForMaskedLM'],
+        tags=['bert']))
+
+
+class GTEBertLoader(ModelLoader):
+
+    def get_model(self, model_dir: str, *args, **kwargs) -> PreTrainedModel:
+        self.auto_model_cls = self.auto_model_cls or AutoModel
+        model = super().get_model(model_dir, *args, **kwargs)
+
+        def _normalizer_hook(module, input, output):
+            output.last_hidden_state = F.normalize(output.last_hidden_state[:, 0], p=2, dim=1)
+            return output
+
+        model.register_forward_hook(_normalizer_hook)
+        return model
+
+
+register_model(
+    ModelMeta(
+        BertModelType.modern_bert_gte,
+        [ModelGroup([
+            Model('iic/gte-modernbert-base', 'Alibaba-NLP/gte-modernbert-base'),
+        ])],
+        GTEBertLoader,
+        template=TemplateType.dummy,
+        requires=['transformers>=4.48'],
+        architectures=['ModernBertModel'],
+        tags=['bert', 'embedding']))
+
+
+class GTEBertReranker(ModelLoader):
+
+    def get_model(self, model_dir: str, *args, **kwargs) -> PreTrainedModel:
+        self.auto_model_cls = self.auto_model_cls or AutoModelForSequenceClassification
+        return super().get_model(model_dir, *args, **kwargs)
+
+
+register_model(
+    ModelMeta(
+        LLMModelType.modern_bert_gte_reranker,
+        [ModelGroup([
+            Model('iic/gte-reranker-modernbert-base', 'Alibaba-NLP/gte-reranker-modernbert-base'),
+        ])],
+        GTEBertReranker,
+        template=TemplateType.bert,
+        requires=['transformers>=4.48'],
+        architectures=['ModernBertForSequenceClassification'],
+        task_type='reranker',
+        tags=['bert', 'reranker']))
+
+register_model(
+    ModelMeta(
+        BertModelType.bert, [ModelGroup([
+            Model('iic/nlp_structbert_backbone_base_std'),
+        ])],
+        template=TemplateType.dummy,
+        tags=['bert']))