初始化项目，由ModelHub XC社区提供模型

Model: mkd-hossain/keural-dpo-5500
Source: Original Platform

modeling_keural.py

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+"""
+KeuralMoECausalLM — Keural Mixture-of-Experts Causal Language Model.
+
+Bilingual Korean-English MoE LLM trained entirely from scratch.
+Developed by MKD Corp AI Research, Republic of Korea.
+
+Architecture:
+  - 14.83B total parameters (~7.42B active per token)
+  - 24 layers, hidden=4096, GQA 32/8 heads
+  - 8 experts per layer, top-2 routing
+  - Sliding window attention (512, alternating layers)
+  - RoPE theta=500,000, context length=4096
+  - Vocabulary: 131,074 tokens (131,072 SPM + <|im_start|> + <|im_end|>)
+
+Load with trust_remote_code=True:
+  from transformers import AutoModelForCausalLM, AutoTokenizer
+  model = AutoModelForCausalLM.from_pretrained(
+      "mkd-hossain/keural-sft3-final",
+      torch_dtype="bfloat16",
+      device_map="auto",
+      trust_remote_code=True,
+  )
+"""
+
+from transformers import MixtralForCausalLM
+from transformers.utils import logging
+
+try:
+    from configuration_keural import KeuralConfig
+except ImportError:
+    from .configuration_keural import KeuralConfig
+
+logger = logging.get_logger(__name__)
+
+
+class KeuralMoECausalLM(MixtralForCausalLM):
+    """
+    Keural MoE Causal Language Model.
+    Bilingual Korean-English 14.83B MoE LLM trained from scratch by MKD Corp AI Research.
+    """
+
+    config_class = KeuralConfig
+    _keys_to_ignore_on_load_missing = ["lm_head.weight"]