Codex-generated pull request

crates/claude-core/src/config.rs

@@ -1,42 +1,42 @@
-use serde::{Deserialize, Serialize};
-
-#[derive(Debug, Clone, Serialize, Deserialize)]
-pub struct ModelConfig {
-    /// Dimension of the token embeddings (and internal transformer states).
-    pub n_embd: i64,
-    /// Number of attention heads.
-    pub n_head: i64,
-    /// Number of transformer layers.
-    pub n_layer: i64,
-    /// Size of the vocabulary.
-    pub vocab_size: i64,
-    /// Maximum context window size (max sequence length).
-    pub max_seq_len: i64,
-    /// Dropout probability (applied to attention and residual connections).
-    pub dropout: f64,
-    /// RMSNorm epsilon value (for numerical stability).
-    pub layer_norm_epsilon: f64,
-    /// Whether to use bias in linear layers (typically false in modern LLMs like Llama/PaLM).
-    pub use_bias: bool,
-}
-
-impl Default for ModelConfig {
-    fn default() -> Self {
-        Self {
-            n_embd: 768, // GPT-2 Small equivalent
-            n_head: 12,
-            n_layer: 12,
-            vocab_size: 50257,
-            max_seq_len: 1024,
-            dropout: 0.0,
-            layer_norm_epsilon: 1e-5,
-            use_bias: false, 
-        }
-    }
-}
-
-impl ModelConfig {
-    pub fn head_size(&self) -> i64 {
-        self.n_embd / self.n_head
-    }
-}
+use serde::{Deserialize, Serialize};
+
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct ModelConfig {
+    /// Dimension of the token embeddings (and internal transformer states).
+    pub n_embd: i64,
+    /// Number of attention heads.
+    pub n_head: i64,
+    /// Number of transformer layers.
+    pub n_layer: i64,
+    /// Size of the vocabulary.
+    pub vocab_size: i64,
+    /// Maximum context window size (max sequence length).
+    pub max_seq_len: i64,
+    /// Dropout probability (applied to attention and residual connections).
+    pub dropout: f64,
+    /// RMSNorm epsilon value (for numerical stability).
+    pub layer_norm_epsilon: f64,
+    /// Whether to use bias in linear layers (typically false in modern LLMs like Llama/PaLM).
+    pub use_bias: bool,
+}
+
+impl Default for ModelConfig {
+    fn default() -> Self {
+        Self {
+            n_embd: 768, // GPT-2 Small equivalent
+            n_head: 12,
+            n_layer: 12,
+            vocab_size: 50257,
+            max_seq_len: 2048,
+            dropout: 0.0,
+            layer_norm_epsilon: 1e-5,
+            use_bias: false,
+        }
+    }
+}
+
+impl ModelConfig {
+    pub fn head_size(&self) -> i64 {
+        self.n_embd / self.n_head
+    }
+}