Update README.md and config.json for Transformers v5

README.md

@@ -46,7 +46,7 @@ library_name: transformers
 
 
 <div align="center">
-<table><tr><td>🆓 <span style="color: orange"> <b>Free API until Jan 28th, 2026</b>! </span> Try on ⬆️ FriendliAI ✈️</td></tr></table>
+<table><tr><td>🆓 <span style="color: orange"> <b>Free API until Feb 12th, 2026</b>! </span> Try on ⬆️ FriendliAI ✈️</td></tr></table>
 </div>
 
 <br>
@@ -380,12 +380,11 @@ The following table shows the evaluation results of the K-EXAONE model in reason
 
 ## Requirements
 
-Until the libraries officially support K-EXAONE, you need to install the requirements in our version with the EXAONE-MoE implementations. We will announce when these libraries are updated to support the K-EXAONE model.
+K-EXAONE is supported by multiple libraries. Please install the required libraries as needed for your use case.
 
 #### Transformers
 
-You can install the latest version of Transformers with support for EXAONE-MoE architecture from [this repository](https://github.com/nuxlear/transformers/tree/add-exaone-moe).
-The base version of Transformers is `5.0.0rc1`, so it might be helpful to check [the migration guide](https://github.com/huggingface/transformers/blob/main/MIGRATION_GUIDE_V5.md) from the Transformers library.
+You should install `transformers >= 5.1.0` for the K-EXAONE model.
 
 #### vLLM
 
@@ -393,8 +392,12 @@ To serve the K-EXAONE model on a vLLM server, you should install both Transforme
 
 #### SGLang
 
-You should install both Transformers and SGLang to use K-EXAONE model on SGLang server.
-You can install the latest version of SGLang with support for EXAONE-MoE architecture from [this repository](https://github.com/xvyaward/sglang/tree/exaone_moe_official).
+You should install both Transformers and SGLang to serve the K-EXAONE model on SGLang server.
+You can install the latest version of SGLang from source using the following commands.
+```bash
+git clone https://github.com/sgl-project/sglang.git
+pip install -e sglang/python
+```
 
 #### llama.cpp
 
@@ -403,7 +406,7 @@ To use the K-EXAONE model with llama.cpp library, you should install `llama.cpp
 
 ## Quickstart
 
-You can use the K-EXAONE model with the Transformers library. For better quality, you should check the [usage guideline](#usage-guideline) section.
+You can use the K-EXAONE model with the Transformers library version `5.1.0` or later.
 
 ### Reasoning mode
 
@@ -584,7 +587,7 @@ vllm serve LGAI-EXAONE/K-EXAONE-236B-A23B \
 
 ### SGLang
 
-We support the K-EXAONE model on SGLang. You need to install our fork of the SGLang library to use the K-EXAONE model. Please check the [requirements](#requirements) section.
+We support the K-EXAONE model on SGLang. You need to install the latest version of the SGLang library from source. Please check the [requirements](#requirements) section.
 Practically, you can serve the model with a 256K context length using tensor parallel on 4 H200 GPUs.
 
 ```bash

config.json

@@ -12,56 +12,6 @@
   "hidden_size": 6144,
   "initializer_range": 0.02,
   "intermediate_size": 18432,
-  "is_moe_layer": [
-    false,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true,
-    true
-  ],
   "layer_types": [
     "sliding_attention",
     "sliding_attention",
@@ -113,6 +63,56 @@
     "full_attention"
   ],
   "max_position_embeddings": 262144,
+  "mlp_layer_types": [
+    "dense",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse",
+    "sparse"
+  ],
   "model_type": "exaone_moe",
   "moe_intermediate_size": 2048,
   "n_group": 1,
@@ -137,7 +137,7 @@
   "tie_word_embeddings": false,
   "tokenizer_class": "GPT2Tokenizer",
   "topk_group": 1,
-  "transformers_version": "5.0.0.dev0",
+  "transformers_version": "5.1.0",
   "use_cache": true,
   "vocab_size": 153600
 }