Adding Sentence Transformers files & update README

1_Pooling/config.json

@@ -3,5 +3,8 @@
   "pooling_mode_cls_token": true,
   "pooling_mode_mean_tokens": false,
   "pooling_mode_max_tokens": false,
-  "pooling_mode_mean_sqrt_len_tokens": false
+  "pooling_mode_mean_sqrt_len_tokens": false,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false,
+  "include_prompt": true
 }

README.md

@@ -2636,9 +2636,7 @@ from sentence_transformers import models, SentenceTransformer
 from sentence_transformers.util import cos_sim
 
 # 1. load model with `cls` pooling
-word_embedding_model = models.Transformer("mixedbread-ai/mxbai-embed-2d-large-v1")
-pooling_model = models.Pooling(word_embedding_model.get_word_embedding_dimension(), pooling_mode="cls")
-model = SentenceTransformer(modules=[word_embedding_model, pooling_model])
+model = SentenceTransformer("mixedbread-ai/mxbai-embed-2d-large-v1")
 
 # 2. set adaptive layer and embedding size.
 # it is recommended to set layers from 20 to 24.

config_sentence_transformers.json

@@ -0,0 +1,9 @@
+{
+  "__version__": {
+    "sentence_transformers": "2.5.1",
+    "transformers": "4.37.0",
+    "pytorch": "2.1.0+cu121"
+  },
+  "prompts": {},
+  "default_prompt_name": null
+}

modules.json

@@ -0,0 +1,14 @@
+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 512,
+  "do_lower_case": false
+}