model: correctly support input vision for deepseek4 (#28154)
* model: correctly support input vision for deepseek4 * nits
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@@ -578,8 +578,7 @@ class DeepseekV4Model(TextModel):
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@classmethod
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def filter_tensors(cls, item: tuple[str, Callable[[], Tensor]]) -> tuple[str, Callable[[], Tensor]] | None:
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name, gen = item
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if (name.startswith(("aligner.", "image_"))
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or name.endswith(".ffn.gate.bias_vl")):
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if name.startswith(("aligner.", "image_")):
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return None
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if name.startswith("mtp."):
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if not cls.mtp_only:
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@@ -856,6 +855,7 @@ class DeepseekV4Model(TextModel):
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"ffn_norm.weight": (gguf.MODEL_TENSOR.FFN_NORM, ".weight"),
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"ffn.gate.weight": (gguf.MODEL_TENSOR.FFN_GATE_INP, ".weight"),
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"ffn.gate.bias": (gguf.MODEL_TENSOR.FFN_EXP_PROBS_B, ".bias"),
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"ffn.gate.bias_vl": (gguf.MODEL_TENSOR.FFN_EXP_PROBS_B_VL, ".bias"),
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"ffn.gate.tid2eid": (gguf.MODEL_TENSOR.FFN_GATE_TID2EID, ".weight"),
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"ffn.shared_experts.w1.weight": (gguf.MODEL_TENSOR.FFN_GATE_SHEXP, ".weight"),
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"ffn.shared_experts.w2.weight": (gguf.MODEL_TENSOR.FFN_DOWN_SHEXP, ".weight"),
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@@ -881,6 +881,10 @@ class DeepseekV4Model(TextModel):
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if re.match(r"layers\.\d+\.ffn\.experts\.\d+\.w[123]\.(weight|scale)$", name):
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return []
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# hash layers route text tokens via tid2eid and image tokens via bias_vl; gate.bias is unused
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if name.endswith(".ffn.gate.bias") and bid is not None and bid < self.hparams["num_hash_layers"]:
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return []
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tensor_key, suffix = self._map_dsv4_tensor_name(name, bid)
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if tensor_key == gguf.MODEL_TENSOR.FFN_GATE_TID2EID:
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return []
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