make qwen-4b default

app.py

@@ -59,7 +59,10 @@ MODELS = {
     #     "repo_id": "unsloth/gpt-oss-20b-BF16",
     #     "description": "A 20B-parameter open-source GPT-style language model quantized to INT4 using AutoRound, with FP8 key-value cache for efficient inference. Optimized for performance and memory efficiency on Intel hardware while maintaining strong language generation capabilities."
     # },
-    
+    "Qwen3-4B-Instruct-2507": {
+        "repo_id": "Qwen/Qwen3-4B-Instruct-2507",
+        "description": "Updated non-thinking instruct variant of Qwen3-4B with 4.0B parameters, featuring significant improvements in instruction following, logical reasoning, multilingualism, and 256K long-context understanding. Strong performance across knowledge, coding, alignment, and agent benchmarks."
+    },    
     "Apriel-1.5-15b-Thinker": {
         "repo_id": "ServiceNow-AI/Apriel-1.5-15b-Thinker",
         "description": "Multimodal reasoning model with 15B parameters, trained via extensive mid-training on text and image data, and fine-tuned only on text (no image SFT). Achieves competitive performance on reasoning benchmarks like Artificial Analysis (score: 52), Tau2 Bench Telecom (68), and IFBench (62). Supports both text and image understanding, fits on a single GPU, and includes structured reasoning output with tool and function calling capabilities."
@@ -99,10 +102,7 @@ MODELS = {
         "repo_id": "Qwen/Qwen3-4B",
         "description": "Dense causal language model with 4.0 B total parameters (3.6 B non-embedding), 36 layers, 32 query heads & 8 KV heads, native 32 768-token context (extendable to 131 072 via YaRN), balanced mid-range capacity & long-context reasoning."
     },
-    "Qwen3-4B-Instruct-2507": {
-        "repo_id": "Qwen/Qwen3-4B-Instruct-2507",
-        "description": "Updated non-thinking instruct variant of Qwen3-4B with 4.0B parameters, featuring significant improvements in instruction following, logical reasoning, multilingualism, and 256K long-context understanding. Strong performance across knowledge, coding, alignment, and agent benchmarks."
-    },
+
     "Gemma-3-4B-IT": {
         "repo_id": "unsloth/gemma-3-4b-it",
         "description": "Gemma-3-4B-IT"