Update tiny models for VisionTextDualEncoderModel-vit-bert

config.json

@@ -1,5 +1,6 @@
 {
   "_commit_hash": null,
+  "_name_or_path": "tiny_models/vision-text-dual-encoder/VisionTextDualEncoderModel-vit-bert",
   "architectures": [
     "VisionTextDualEncoderModel"
   ],
@@ -7,7 +8,7 @@
   "model_type": "vision-text-dual-encoder",
   "projection_dim": 512,
   "text_config": {
-    "_name_or_path": "/tmp/tmpwmqhff1f/decoder/BertModel",
+    "_name_or_path": "/tmp/tmpbgs85kmg/decoder/BertModel",
     "add_cross_attention": false,
     "architectures": [
       "BertModel"
@@ -80,7 +81,7 @@
     "top_p": 1.0,
     "torch_dtype": "float32",
     "torchscript": false,
-    "transformers_version": "4.25.0.dev0",
+    "transformers_version": "4.28.0.dev0",
     "type_vocab_size": 16,
     "typical_p": 1.0,
     "use_bfloat16": false,
@@ -90,7 +91,7 @@
   "torch_dtype": "float32",
   "transformers_version": null,
   "vision_config": {
-    "_name_or_path": "/tmp/tmpwmqhff1f/encoder/ViTModel",
+    "_name_or_path": "/tmp/tmpbgs85kmg/encoder/ViTModel",
     "add_cross_attention": false,
     "architectures": [
       "ViTModel"
@@ -165,7 +166,7 @@
     "top_p": 1.0,
     "torch_dtype": "float32",
     "torchscript": false,
-    "transformers_version": "4.25.0.dev0",
+    "transformers_version": "4.28.0.dev0",
     "typical_p": 1.0,
     "use_bfloat16": false
   }

preprocessor_config.json

@@ -8,7 +8,7 @@
     0.5,
     0.5
   ],
-  "image_processor_type": "ViTImageProcessor",
+  "image_processor_type": "ViTFeatureExtractor",
   "image_std": [
     0.5,
     0.5,

pytorch_model.bin

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 size 716569

tf_model.h5

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+      "##ハ": 1104,
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+      "##ด": 1106,
+      "##ܠ": 1107,
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+      "##サ": 1120,
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+      "##œ": 1123
     }
   }
 }

tokenizer_config.json

@@ -1,10 +1,10 @@
 {
+  "clean_up_tokenization_spaces": true,
   "cls_token": "[CLS]",
   "do_basic_tokenize": true,
   "do_lower_case": true,
   "mask_token": "[MASK]",
   "model_max_length": 512,
-  "name_or_path": "/tmp/tmpwmqhff1f/decoder/processors",
   "never_split": null,
   "pad_token": "[PAD]",
   "sep_token": "[SEP]",

vocab.txt

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