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configuration_nanogpt.py

@@ -0,0 +1,26 @@
+from transformers import PretrainedConfig
+
+
+class NanoGPTConfig(PretrainedConfig):
+    model_type = "nanogpt"
+
+    def __init__(
+        self,
+        sequence_len: int = 1024,
+        vocab_size: int = 50304,
+        n_layer: int = 12,
+        n_head: int = 6,
+        n_kv_head: int = 6,
+        n_embd: int = 768,
+        **kwargs,
+    ):
+        self.sequence_len = sequence_len
+        self.vocab_size = vocab_size
+        self.n_layer = n_layer
+        self.n_head = n_head
+        self.n_kv_head = n_kv_head
+        self.n_embd = n_embd
+        super().__init__(**kwargs)
+
+
+