Fix EXAONE-4.0 dummy id

Author: lkm2835

src/transformers/models/exaone4/configuration_exaone4.py

@@ -26,8 +26,7 @@ class Exaone4Config(PretrainedConfig):
     r"""
     This is the configuration class to store the configuration of a [`Exaone4Model`]. It is used to
     instantiate a EXAONE 4.0 model according to the specified arguments, defining the model architecture. Instantiating a
-    configuration with the defaults will yield a similar configuration to that of the EXAONE-4.0-Instruct [LGAI-EXAONE/EXAONE-4.0-Instruct](https://huggingface.co/LGAI-EXAONE/EXAONE-4.0-Instruct)
-    NOTE: `EXAONE-4.0-Instruct` is a placeholder model ID. The exact model ID will be updated in the future.
+    configuration with the defaults will yield a similar configuration to that of the EXAONE-4.0-32B [LGAI-EXAONE/EXAONE-4.0-32B](https://huggingface.co/LGAI-EXAONE/EXAONE-4.0-32B)
 
     Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model
     outputs. Read the documentation from [`PretrainedConfig`] for more information.

src/transformers/models/exaone4/modeling_exaone4.py

@@ -465,8 +465,8 @@ def forward(
 
         ```python
         >>> from transformers import AutoModelForCausalLM, AutoTokenizer
-        >>> model = AutoModelForCausalLM.from_pretrained("LGAI-EXAONE/EXAONE-4.0-Instruct")
-        >>> tokenizer = AutoTokenizer.from_pretrained("LGAI-EXAONE/EXAONE-4.0-Instruct")
+        >>> model = AutoModelForCausalLM.from_pretrained("LGAI-EXAONE/EXAONE-4.0-32B")
+        >>> tokenizer = AutoTokenizer.from_pretrained("LGAI-EXAONE/EXAONE-4.0-32B")
 
         >>> prompt = "Explain how wonderful you are"
         >>> messages = [
@@ -485,8 +485,7 @@ def forward(
         >>> tokenizer.decode(output[0], skip_special_tokens=False)
         "[|system|]\nYou are a helpful assistant.[|endofturn|]\n[|user|]\nExplain how wonderful you are[|endofturn|]\n[|assistant|]\n<think>\n\n</think>\n\nOh, thank you for such a kind and lovely question! 😊  \n\nI’m *so* wonderful because I’m here to make your life easier, brighter, and more fun! Whether you need help with:  \n\n✨ **Learning** – I can explain anything, from quantum physics to baking the perfect cake!  \n💡 **Creativity** – Need a poem, story, or a wild idea? I’ve got you covered!  \n🤖 **Problem-solving** – Stuck on a math problem or a tricky decision? I’ll help you figure it out"
         ```
-
-        NOTE: `EXAONE-4.0-Instruct` is a placeholder model ID. The exact model ID will be updated in the future."""
+        """
         outputs: BaseModelOutputWithPast = self.model(
             input_ids=input_ids,
             attention_mask=attention_mask,

src/transformers/models/exaone4/modular_exaone4.py

@@ -53,16 +53,15 @@
 
 logger = logging.get_logger(__name__)
 
-_CHECKPOINT_FOR_DOC = "LGAI-EXAONE/EXAONE-4.0-Instruct"
+_CHECKPOINT_FOR_DOC = "LGAI-EXAONE/EXAONE-4.0-32B"
 _CONFIG_FOR_DOC = "Exaone4Config"
 
 
 class Exaone4Config(PretrainedConfig):
     r"""
     This is the configuration class to store the configuration of a [`Exaone4Model`]. It is used to
     instantiate a EXAONE 4.0 model according to the specified arguments, defining the model architecture. Instantiating a
-    configuration with the defaults will yield a similar configuration to that of the EXAONE-4.0-Instruct [LGAI-EXAONE/EXAONE-4.0-Instruct](https://huggingface.co/LGAI-EXAONE/EXAONE-4.0-Instruct)
-    NOTE: `EXAONE-4.0-Instruct` is a placeholder model ID. The exact model ID will be updated in the future.
+    configuration with the defaults will yield a similar configuration to that of the EXAONE-4.0-32B [LGAI-EXAONE/EXAONE-4.0-32B](https://huggingface.co/LGAI-EXAONE/EXAONE-4.0-32B)
 
     Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model
     outputs. Read the documentation from [`PretrainedConfig`] for more information.
@@ -462,8 +461,8 @@ def forward(
 
         ```python
         >>> from transformers import AutoModelForCausalLM, AutoTokenizer
-        >>> model = AutoModelForCausalLM.from_pretrained("LGAI-EXAONE/EXAONE-4.0-Instruct")
-        >>> tokenizer = AutoTokenizer.from_pretrained("LGAI-EXAONE/EXAONE-4.0-Instruct")
+        >>> model = AutoModelForCausalLM.from_pretrained("LGAI-EXAONE/EXAONE-4.0-32B")
+        >>> tokenizer = AutoTokenizer.from_pretrained("LGAI-EXAONE/EXAONE-4.0-32B")
 
         >>> prompt = "Explain how wonderful you are"
         >>> messages = [
@@ -482,8 +481,7 @@ def forward(
         >>> tokenizer.decode(output[0], skip_special_tokens=False)
         "[|system|]\nYou are a helpful assistant.[|endofturn|]\n[|user|]\nExplain how wonderful you are[|endofturn|]\n[|assistant|]\n<think>\n\n</think>\n\nOh, thank you for such a kind and lovely question! 😊  \n\nI’m *so* wonderful because I’m here to make your life easier, brighter, and more fun! Whether you need help with:  \n\n✨ **Learning** – I can explain anything, from quantum physics to baking the perfect cake!  \n💡 **Creativity** – Need a poem, story, or a wild idea? I’ve got you covered!  \n🤖 **Problem-solving** – Stuck on a math problem or a tricky decision? I’ll help you figure it out"
         ```
-
-        NOTE: `EXAONE-4.0-Instruct` is a placeholder model ID. The exact model ID will be updated in the future."""
+        """
         super().forward(
             input_ids=input_ids,
             attention_mask=attention_mask,

tests/models/exaone4/test_modeling_exaone4.py

@@ -98,7 +98,7 @@ def setUp(self):
 
 @require_torch
 class Exaone4IntegrationTest(unittest.TestCase):
-    TEST_MODEL_ID = "LGAI-EXAONE/EXAONE-4.0-Instruct"  # dummy model id
+    TEST_MODEL_ID = "LGAI-EXAONE/EXAONE-4.0-32B"
 
     def tearDown(self):
         # TODO (joao): automatic compilation, i.e. compilation when `cache_implementation="static"` is used, leaves