Upload config

config.json

@@ -1,4 +1,7 @@
 {
+  "auto_map": {
+    "AutoConfig": "configuration_mamba.MambaConfig"
+  },
   "d_model": 768,
   "fused_add_norm": true,
   "model_type": "mamba",

configuration_mamba.py

@@ -0,0 +1,30 @@
+import mamba_ssm
+from transformers import AutoConfig, AutoModel, AutoModelForCausalLM, AutoTokenizer, PretrainedConfig, PreTrainedModel
+
+mamba_config_defaults = mamba_ssm.models.config_mamba.MambaConfig()
+
+class MambaConfig(PretrainedConfig):
+    model_type = "mamba"
+
+    def __init__(
+        self,
+        d_model: int = mamba_config_defaults.d_model,
+        fused_add_norm: bool = mamba_config_defaults.fused_add_norm,
+        n_layer: int = mamba_config_defaults.n_layer,
+        pad_vocab_size_multiple: int = mamba_config_defaults.pad_vocab_size_multiple,
+        residual_in_fp32: bool = mamba_config_defaults.residual_in_fp32,
+        rms_norm: bool = mamba_config_defaults.rms_norm,
+        ssm_cfg: dict = mamba_config_defaults.ssm_cfg,
+        vocab_size: int = mamba_config_defaults.vocab_size,
+        **kwargs,
+    ):
+        self.d_model = d_model
+        self.fused_add_norm = fused_add_norm
+        self.n_layer = n_layer
+        self.pad_vocab_size_multiple = pad_vocab_size_multiple
+        self.residual_in_fp32 = residual_in_fp32
+        self.rms_norm = rms_norm
+        self.ssm_cfg = ssm_cfg
+        self.vocab_size = vocab_size
+
+        super().__init__(**kwargs)