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convert-hf : check for unprocessed Jamba experts
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@ -2470,6 +2470,15 @@ class JambaModel(Model):
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yield new_name, data_torch
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def write_tensors(self):
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super().write_tensors()
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if self._experts is not None:
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# flatten `list[dict[str, Tensor]]` into `list[str]`
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experts = [k for d in self._experts for k in d.keys()]
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if len(experts) > 0:
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raise ValueError(f"Unprocessed experts: {experts}")
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# same as Mamba
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def extra_f32_tensors(self, name: str, new_name: str, bid: int | None, n_dims: int) -> bool:
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del n_dims # unused
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