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convert-llama-h5-to-gguf.py : add 70b gqa support
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@ -1,4 +1,4 @@
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# HF llama --> gguf conversion, GQA/70b not supported
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# HF llama --> gguf conversion
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import gguf
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import gguf_namemap as tmap
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@ -10,7 +10,7 @@ import json
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import numpy as np
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import torch
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from typing import Any, List
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from typing import Any, List, Optional
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from pathlib import Path
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from sentencepiece import SentencePieceProcessor
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@ -18,11 +18,11 @@ from sentencepiece import SentencePieceProcessor
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# compatible with python < 3.9
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NDArray: 'TypeAlias' = 'np.ndarray[Any, Any]'
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def permute(weights: NDArray, n_head: int) -> NDArray:
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def permute(weights: NDArray, n_head: int, n_kv_head: Optional[int] = None) -> NDArray:
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if n_kv_head is not None and n_head != n_kv_head: n_head //= n_kv_head
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return (weights.reshape(n_head, 2, weights.shape[0] // n_head // 2, *weights.shape[1:])
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.swapaxes(1, 2)
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.reshape(weights.shape))
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.swapaxes(1, 2)
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.reshape(weights.shape))
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def count_model_parts(dir_model: str) -> int:
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num_parts = 0
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@ -220,7 +220,7 @@ for part_name in part_names:
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# permute these
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if name.endswith(".q_proj.weight") or name.endswith(".k_proj.weight"):
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data = permute(data,head_count)
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data = permute(data, head_count, head_count_kv)
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# map tensor names
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if name.endswith(".weight") and name[:-7] in tensor_map:
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@ -289,7 +289,7 @@ for part_name in part_names:
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# permute these
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if name.endswith(".q_proj.weight") or name.endswith(".k_proj.weight"):
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data = permute(data, head_count)
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data = permute(data, head_count, head_count_kv)
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# map tensor names
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if name.endswith(".weight") and name[:-7] in tensor_map:
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