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configuration_quark.py

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+from transformers import PretrainedConfig
+
+class QuarkConfig(PretrainedConfig):
+    model_type = "quark"
+    def __init__(self, vocab_size=65537, d_model=768, n_heads=12, n_kv_heads=4,
+                 n_layers=32, d_ff=2048, head_dim=64, max_seq_len=2048,
+                 rope_theta=10000.0, rms_eps=1e-5, qkv_bias=True, dropout=0.0, **kwargs):
+        self.vocab_size=vocab_size; self.d_model=d_model; self.n_heads=n_heads
+        self.n_kv_heads=n_kv_heads; self.n_layers=n_layers; self.d_ff=d_ff
+        self.head_dim=head_dim; self.max_seq_len=max_seq_len; self.rope_theta=rope_theta
+        self.rms_eps=rms_eps; self.qkv_bias=qkv_bias; self.dropout=dropout
+        super().__init__(**kwargs)