secret

src/exo/shared/models/model_cards.py

@@ -16,19 +16,19 @@ class ModelCard(CamelCaseModel):
 
 MODEL_CARDS: dict[str, ModelCard] = {
     # kimi k2
-    "kimi-k2:4bit": ModelCard(
-        short_id="kimi-k2:4bit",
-        model_id="mlx-community/Kimi-K2-Instruct-4bit",
-        name="Kimi K2 (4-bit)",
-        description="""Kimi K2 is a state-of-the-art mixture-of-experts (MoE) language model with 32 billion activated parameters and 1 trillion total parameters. Trained with the Muon optimizer, Kimi K2 achieves exceptional performance across frontier knowledge, reasoning, and coding tasks while being meticulously optimized for agentic capabilities.""",
-        tags=[],
-        metadata=ModelMetadata(
-            model_id=ModelId("mlx-community/Kimi-K2-Instruct-4bit"),
-            pretty_name="Kimi K2 (4-bit)",
-            storage_size=Memory.from_kb(536870912),
-            n_layers=61,
-        ),
-    ),
+    # "kimi-k2:4bit": ModelCard(
+    #     short_id="kimi-k2:4bit",
+    #     model_id="mlx-community/Kimi-K2-Instruct-4bit",
+    #     name="Kimi K2 (4-bit)",
+    #     description="""Kimi K2 is a state-of-the-art mixture-of-experts (MoE) language model with 32 billion activated parameters and 1 trillion total parameters. Trained with the Muon optimizer, Kimi K2 achieves exceptional performance across frontier knowledge, reasoning, and coding tasks while being meticulously optimized for agentic capabilities.""",
+    #     tags=[],
+    #     metadata=ModelMetadata(
+    #         model_id=ModelId("mlx-community/Kimi-K2-Instruct-4bit"),
+    #         pretty_name="Kimi K2 (4-bit)",
+    #         storage_size=Memory.from_kb(536870912),
+    #         n_layers=61,
+    #     ),
+    # ),
 
     # deepseek v3
     "deepseek-v3-0324:4bit": ModelCard(