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convert.py : fix baichuan7B support (#2870)
* [Fix]: convert.py support baichuan7B * convert.py : fix trailing whitespaces --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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@ -469,7 +469,7 @@ class UnquantizedTensor(Tensor):
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def permute_part(self, n_part: int, n_head: int) -> 'UnquantizedTensor':
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r = self.ndarray.shape[0] // 3
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return UnquantizedTensor(permute(self.ndarray[r * n_part : r * n_part + r, ...], n_head))
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return UnquantizedTensor(permute(self.ndarray[r * n_part : r * n_part + r, ...], n_head, n_head))
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def part(self, n_part: int) -> 'UnquantizedTensor':
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r = self.ndarray.shape[0] // 3
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@ -952,9 +952,10 @@ def convert_model_names(model: LazyModel, params: Params) -> LazyModel:
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#tmp[f"model.layers.{i}.self_attn.v_proj.weight"] = model[f"model.layers.{i}.self_attn.v_proj.weight"]
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elif f"model.layers.{i}.self_attn.W_pack.weight" in model:
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print(f"Unpacking and permuting layer {i}")
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tmp[f"model.layers.{i}.self_attn.q_proj.weight"] = permute_part_lazy(model[f"model.layers.{i}.self_attn.W_pack.weight"], 0, params.n_head, params.n_head)
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tmp[f"model.layers.{i}.self_attn.k_proj.weight"] = permute_part_lazy(model[f"model.layers.{i}.self_attn.W_pack.weight"], 1, params.n_head, params.n_head_kv)
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tmp[f"model.layers.{i}.self_attn.q_proj.weight"] = permute_part_lazy(model[f"model.layers.{i}.self_attn.W_pack.weight"], 0, params.n_head)
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tmp[f"model.layers.{i}.self_attn.k_proj.weight"] = permute_part_lazy(model[f"model.layers.{i}.self_attn.W_pack.weight"], 1, params.n_head)
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tmp[f"model.layers.{i}.self_attn.v_proj.weight"] = part_lazy (model[f"model.layers.{i}.self_attn.W_pack.weight"], 2)
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del tmp[f"model.layers.{i}.self_attn.W_pack.weight"]
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else:
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break
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