Add HuggingFace format support for OmniLottie

configuration_lottie_decoder.py

@@ -0,0 +1,54 @@
+"""
+OmniLottie Decoder Configuration
+"""
+from transformers import PretrainedConfig
+from typing import Optional
+
+
+class LottieDecoderConfig(PretrainedConfig):
+    """
+    Configuration class for LottieDecoder model, inheriting from PretrainedConfig
+
+    Stores configuration parameters for the LottieDecoder model,
+    supporting Hugging Face's standard save and load mechanisms.
+
+    Args:
+        pix_len (int): Maximum length for image/video tokens, default 4560
+        text_len (int): Maximum length for text tokens, default 1500
+        base_model_path (str): Path or name of base Qwen2.5-VL model
+        vocab_size (int): Vocabulary size, extended to 192400 to support Lottie tokens
+        bos_token_id (int): Beginning-of-sequence token ID for Lottie
+        eos_token_id (int): End-of-sequence token ID for Lottie
+        pad_token_id (int): Padding token ID
+        torch_dtype (str): Model weight data type, default "bfloat16"
+        attn_implementation (str): Attention implementation method, default "eager"
+    """
+
+    model_type = "lottie_decoder"
+
+    def __init__(
+        self,
+        pix_len: int = 4560,
+        text_len: int = 1500,
+        base_model_path: str = "Qwen/Qwen2.5-VL-3B-Instruct",
+        vocab_size: int = 192400,
+        bos_token_id: int = 192398,
+        eos_token_id: int = 192399,
+        pad_token_id: int = 151643,
+        torch_dtype: str = "bfloat16",
+        attn_implementation: str = "eager",
+        **kwargs
+    ):
+        super().__init__(
+            bos_token_id=bos_token_id,
+            eos_token_id=eos_token_id,
+            pad_token_id=pad_token_id,
+            **kwargs
+        )
+
+        self.pix_len = pix_len
+        self.text_len = text_len
+        self.base_model_path = base_model_path
+        self.vocab_size = vocab_size
+        self.torch_dtype = torch_dtype
+        self.attn_implementation = attn_implementation