Update model.py

model.py

@@ -0,0 +1,40 @@
+from transformers import PretrainedConfig, PreTrainedModel
+
+class DiffusionConfig(PretrainedConfig):
+    """Configuration class for Diffusion-LLM model."""
+    model_type = "diffusionLM"
+    
+    def __init__(
+        self,
+        vocab_size: int = 50257,
+        hidden_size: int = 768,
+        num_hidden_layers: int = 12,
+        num_attention_heads: int = 12,
+        intermediate_size: int = 3072,
+        hidden_dropout_prob: float = 0.1,
+        attention_probs_dropout_prob: float = 0.1,
+        max_position_embeddings: int = 1024,
+        initializer_range: float = 0.02,
+        layer_norm_eps: float = 1e-12,
+        pad_token_id: int = 0,
+        mask_token_id: int = 50256,
+        eos_token_id: int = 50256,
+        num_timesteps: int = 100,
+        time_embed_dim: int = 128,
+        **kwargs
+    ):
+        super().__init__(pad_token_id=pad_token_id, **kwargs)
+        self.vocab_size = vocab_size
+        self.hidden_size = hidden_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads 
+        self.intermediate_size = intermediate_size
+        self.hidden_dropout_prob = hidden_dropout_prob
+        self.attention_probs_dropout_prob = attention_probs_dropout_prob
+        self.max_position_embeddings = max_position_embeddings
+        self.initializer_range = initializer_range
+        self.layer_norm_eps = layer_norm_eps
+        self.mask_token_id = mask_token_id
+        self.eos_token_id = eos_token_id
+        self.num_timesteps = num_timesteps
+        self.time_embed_dim = time_embed_dim