Upload processor

preprocessor_config.json

@@ -3,13 +3,14 @@
     "AutoProcessor": "processing_veld.VELDProcessor"
   },
   "do_normalize": true,
+  "do_rescale": true,
   "do_resize": true,
-  "feature_extractor_type": "ViTFeatureExtractor",
   "image_mean": [
     0.5,
     0.5,
     0.5
   ],
+  "image_processor_type": "ViTImageProcessor",
   "image_std": [
     0.5,
     0.5,
@@ -17,5 +18,9 @@
   ],
   "processor_class": "VELDProcessor",
   "resample": 2,
-  "size": 384
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 384,
+    "width": 384
+  }
 }

processing_veld.py

@@ -24,16 +24,16 @@ class VELDProcessor(ProcessorMixin):
     r"""
     Constructs a VELD processor which wraps a vision feature extractor and a tokenizer into a single
     processor.
-    [`VELDProcessor`] offers all the functionalities of [`AutoFeatureExtractor`] and
+    [`VELDProcessor`] offers all the functionalities of [`AutoImageProcessor`] and
     [`AutoTokenizer`]. See the [`~VELDProcessor.__call__`] and
     [`~VELDProcessor.decode`] for more information.
     Args:
-        feature_extractor ([`AutoFeatureExtractor`]):
+        feature_extractor ([`AutoImageProcessor`]):
             The feature extractor is a required input.
         tokenizer ([`PreTrainedTokenizer`]):
             The tokenizer is a required input.
     """
-    feature_extractor_class = "AutoFeatureExtractor"
+    feature_extractor_class = "AutoImageProcessor"
     tokenizer_class = "AutoTokenizer"
 
     def __init__(self, feature_extractor, tokenizer):
@@ -45,7 +45,7 @@ class VELDProcessor(ProcessorMixin):
         Main method to prepare for the model one or several sequences(s) and image(s). This method forwards the `text`
         and `kwargs` arguments to VisionTextDualEncoderTokenizer's [`~PreTrainedTokenizer.__call__`] if `text` is not
         `None` to encode the text. To prepare the image(s), this method forwards the `images` and `kwrags` arguments to
-        AutoFeatureExtractor's [`~AutoFeatureExtractor.__call__`] if `images` is not `None`. Please refer to the
+        AutoImageProcessor's [`~AutoImageProcessor.__call__`] if `images` is not `None`. Please refer to the
         doctsring of the above two methods for more information.
         Args:
             text (`str`, `List[str]`, `List[List[str]]`):

special_tokens_map.json

@@ -1,107 +1,51 @@
 {
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-  ],
-  "eos_token": "</s>",
-  "pad_token": "<pad>",
-  "unk_token": "<unk>"
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
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+    "single_word": false
+  }
 }

spiece.model

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:edc595fcd800672d6ef0e2aea5ba0f1dc8826471f6f40a87b70619dcc60ddd4a
-size 1466734
+oid sha256:4368e6b7901e8c54bd62326ca5a5063eba36c31d74995a599a5be77a0cd5cfd0
+size 1592581

tokenizer_config.json

@@ -1,117 +1,67 @@
 {
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   "auto_map": {
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-  "model_max_length": 512,
-  "name_or_path": "checkpoints/veld_e1_linear",
-  "pad_token": "<pad>",
+  "bos_token": {
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 }