🔴 [VLM] Add base model without head (#37033)

* i guessreverted all CdGen classes

* style

* llava onevision

* fix copies

* fix some tests

* some more tests

* dump

* skip these

* nevermind, i am dumb

* revert fix not needed

* fixup

* fixup

* another fixup

* more fixup to make ci finally happy

* fixup after rebasing

* fix qwen tests

* add internVL + typos here and there

* image token index -> id

* style

* fix init weights

* revert blip-2 not supported

* address comments

* fix copies

* revert blip2 test file as well

* as discussed internally, revert back CdGen models

* fix some tests

* fix more tests for compile

* CI red

* fix copies

* enumerate explicitly allowed models

* address comments

* fix tests

* fixup

* style again

* add tests for new model class

* another fixup ( x _ x )

* [fixup] unused attributes can be removed post-deprecation

tests/models/gemma3/test_modeling_gemma3.py

@@ -50,6 +50,7 @@ if is_torch_available():
     from transformers import (
         Gemma3ForCausalLM,
         Gemma3ForConditionalGeneration,
+        Gemma3Model,
         Gemma3Processor,
         Gemma3TextModel,
     )
@@ -148,9 +149,9 @@ class Gemma3Vision2TextModelTester:
         self,
         parent,
         mm_tokens_per_image=2,
-        image_token_index=1,
-        boi_token_index=2,
-        eoi_token_index=3,
+        image_token_index=4,
+        boi_token_index=5,
+        eoi_token_index=6,
         seq_length=25,
         is_training=True,
         vision_config={
@@ -242,7 +243,14 @@ class Gemma3Vision2TextModelTester:
 
 @require_torch
 class Gemma3Vision2TextModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
-    all_model_classes = (Gemma3ForConditionalGeneration,) if is_torch_available() else ()
+    all_model_classes = (
+        (
+            Gemma3Model,
+            Gemma3ForConditionalGeneration,
+        )
+        if is_torch_available()
+        else ()
+    )
     all_generative_model_classes = (Gemma3ForConditionalGeneration,) if is_torch_available() else ()
     test_headmasking = False
     test_pruning = False