convert : accept "ExaoneMoeForCausalLM" arch spelling (#26660)
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@@ -70,6 +70,7 @@ TEXT_MODEL_MAP: dict[str, str] = {
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"Exaone4ForCausalLM": "exaone",
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"Exaone4ForCausalLM": "exaone",
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"ExaoneForCausalLM": "exaone",
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"ExaoneForCausalLM": "exaone",
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"ExaoneMoEForCausalLM": "exaone",
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"ExaoneMoEForCausalLM": "exaone",
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"ExaoneMoeForCausalLM": "exaone",
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"FalconForCausalLM": "falcon",
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"FalconForCausalLM": "falcon",
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"FalconH1ForCausalLM": "falcon_h1",
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"FalconH1ForCausalLM": "falcon_h1",
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"FalconMambaForCausalLM": "mamba",
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"FalconMambaForCausalLM": "mamba",
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@@ -123,7 +123,9 @@ class Exaone4Model(TextModel):
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yield (self.format_tensor_name(gguf.MODEL_TENSOR.ROPE_FREQS), torch.tensor(rope_factors, dtype=torch.float32))
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yield (self.format_tensor_name(gguf.MODEL_TENSOR.ROPE_FREQS), torch.tensor(rope_factors, dtype=torch.float32))
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@ModelBase.register("ExaoneMoEForCausalLM")
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# note: transformers >= 5.1 renamed the class to "ExaoneMoeForCausalLM" (lowercase 'e'),
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# so accept both spellings - LG AI have updated the configs of already-released models
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@ModelBase.register("ExaoneMoEForCausalLM", "ExaoneMoeForCausalLM")
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class ExaoneMoEModel(Exaone4Model):
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class ExaoneMoEModel(Exaone4Model):
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model_arch = gguf.MODEL_ARCH.EXAONE_MOE
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model_arch = gguf.MODEL_ARCH.EXAONE_MOE
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