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config.json

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+{
+  "model_type": "lightning",
+  "vocab_size": 65830,
+  "d_model": 256,
+  "nhead": 4,
+  "num_layers": 4,
+  "dropout": 0.1,
+  "max_seq_len": 160,
+  "auto_map": {
+    "AutoConfig": "configuration_lightning.LightningConfig",
+    "AutoModelForCausalLM": "modeling_lightning.LightningForCausalLM"
+  }
+}

configuration_luna copy.py

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+from transformers import PretrainedConfig
+
+
+class LightningConfig(PretrainedConfig):
+    model_type = "lightning"
+
+    def __init__(
+        self,
+        vocab_size=75000,
+        d_model=256,
+        nhead=4,
+        num_layers=6,
+        dropout=0.1,
+        max_seq_len=200,
+        **kwargs
+    ):
+        kwargs.setdefault("tie_word_embeddings", False)
+        super().__init__(**kwargs)
+
+        self.vocab_size = vocab_size
+        self.d_model = d_model
+        self.nhead = nhead
+        self.num_layers = num_layers
+        self.dropout = dropout
+        self.max_seq_len = max_seq_len
+        
+        self.num_hidden_layers = num_layers
+        self.num_attention_heads = nhead
+        self.hidden_size = d_model

configuration_luna.py

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+from transformers import PretrainedConfig
+
+
+class LightningConfig(PretrainedConfig):
+    model_type = "lightning"
+
+    def __init__(
+        self,
+        vocab_size=75000,
+        d_model=256,
+        nhead=4,
+        num_layers=6,
+        dropout=0.1,
+        max_seq_len=200,
+        **kwargs
+    ):
+        kwargs.setdefault("tie_word_embeddings", False)
+        super().__init__(**kwargs)
+
+        self.vocab_size = vocab_size
+        self.d_model = d_model
+        self.nhead = nhead
+        self.num_layers = num_layers
+        self.dropout = dropout
+        self.max_seq_len = max_seq_len
+        
+        self.num_hidden_layers = num_layers
+        self.num_attention_heads = nhead
+        self.hidden_size = d_model

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8ee65b783e97db03f9167748c7f4e636eed773aa48474aabdbef45dece730893
+size 172775680