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llama : add 128k yarn context for Qwen (#10698)
* add 128k yarn context for Qwen * added property for model tensors * removing useless line
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@ -1992,6 +1992,14 @@ class Qwen2Model(Model):
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except FileNotFoundError:
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except FileNotFoundError:
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self._set_vocab_gpt2()
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self._set_vocab_gpt2()
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def set_gguf_parameters(self):
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super().set_gguf_parameters()
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if self.hparams.get("rope_scaling") is not None and "factor" in self.hparams["rope_scaling"]:
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if self.hparams["rope_scaling"].get("type") == "yarn":
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self.gguf_writer.add_rope_scaling_type(gguf.RopeScalingType.YARN)
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self.gguf_writer.add_rope_scaling_factor(self.hparams["rope_scaling"]["factor"])
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self.gguf_writer.add_rope_scaling_orig_ctx_len(self.hparams["rope_scaling"]["original_max_position_embeddings"])
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@Model.register("Qwen2MoeForCausalLM")
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@Model.register("Qwen2MoeForCausalLM")
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class Qwen2MoeModel(Model):
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class Qwen2MoeModel(Model):
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@ -761,6 +761,7 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
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MODEL_TENSOR.TOKEN_EMBD,
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MODEL_TENSOR.TOKEN_EMBD,
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MODEL_TENSOR.OUTPUT_NORM,
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MODEL_TENSOR.OUTPUT_NORM,
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MODEL_TENSOR.OUTPUT,
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MODEL_TENSOR.OUTPUT,
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MODEL_TENSOR.ROPE_FREQS,
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MODEL_TENSOR.ATTN_NORM,
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MODEL_TENSOR.ATTN_NORM,
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MODEL_TENSOR.ATTN_Q,
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MODEL_TENSOR.ATTN_Q,
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MODEL_TENSOR.ATTN_K,
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MODEL_TENSOR.ATTN_K,
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