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100 changes: 100 additions & 0 deletions convert-unversioned-ggml-to-ggml.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,100 @@
#!/usr/bin/env python3
# Original by https://github.com/eiz
# https://github.com/ggerganov/llama.cpp/issues/324#issuecomment-1476227818
import argparse
import glob
import os
import struct
import sys
from sentencepiece import SentencePieceProcessor

HPARAMS = keys = ["vocab_size", "dim", "multiple_of", "n_heads", "n_layers"]

def parse_args():
parser = argparse.ArgumentParser(description='Upgrade old ggml model files to the current format')
parser.add_argument('dir_model', help='directory containing ggml .bin files')
parser.add_argument('tokenizer_model', help='path to LLaMA tokenizer.model file')
return parser.parse_args()

def read_header(f_in):
struct_fmt = "i" * (3 + len(HPARAMS))
struct_size = struct.calcsize(struct_fmt)
buf = f_in.read(struct_size)
return struct.unpack(struct_fmt, buf)

def write_header(f_out, header):
(magic, vocab_size, dim, multiple_of, n_heads, n_layers, rot, ftype) = header

if magic != 0x67676d6c:
raise Exception('Invalid file magic. Must be an old style ggml file.')
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wait im confused, isn't it supposed to be old style ggml file for this?

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It expects the unversioned GGML model and produces the versioned one.
#define LLAMA_FILE_MAGIC_UNVERSIONED 0x67676d6c // pre-versioned files


values = [
0x67676d66, # magic: ggml in hex
1, # file version
vocab_size,
dim,
multiple_of,
n_heads,
n_layers,
rot,
ftype
]
f_out.write(struct.pack("i" * len(values), *values))

def write_tokens(fout, tokenizer):
for i in range(tokenizer.vocab_size()):
if tokenizer.is_unknown(i):
text = " \u2047 ".encode("utf-8")
elif tokenizer.is_control(i):
text = b""
elif tokenizer.is_byte(i):
piece = tokenizer.id_to_piece(i)
if len(piece) != 6:
print(f"Invalid token: {piece}")
sys.exit(1)
byte_value = int(piece[3:-1], 16)
text = struct.pack("B", byte_value)
else:
text = tokenizer.id_to_piece(i).replace("\u2581", " ").encode("utf-8")
fout.write(struct.pack("i", len(text)))
fout.write(text)
fout.write(struct.pack("f", tokenizer.get_score(i)))

def read_tokens(f_in, tokenizer):
for i in range(tokenizer.vocab_size()):
len_b = f_in.read(4)
(length,) = struct.unpack("i", len_b)
f_in.read(length)

def copy_all_data(f_out, f_in):
while True:
buf = f_in.read(1024 * 1024)
if not buf:
break
f_out.write(buf)

def convert_one_file(path_in, tokenizer):
path_tmp = f"{path_in}.tmp"
path_orig= f"{path_in}.orig"
print(f"converting {path_in}")
with open(path_in, "rb") as f_in, open(path_tmp, "wb") as f_out:
write_header(f_out, read_header(f_in))
read_tokens(f_in, tokenizer)
write_tokens(f_out, tokenizer)
copy_all_data(f_out, f_in)
os.rename(path_in, path_orig)
os.rename(path_tmp, path_in)

def main():
args = parse_args()
files = []
files.extend(glob.glob(f"{args.dir_model}/*.bin"))
files.extend(glob.glob(f"{args.dir_model}/*.bin.*"))

tokenizer = SentencePieceProcessor(args.tokenizer_model)

for file in files:
convert_one_file(file, tokenizer)

if __name__ == "__main__":
main()
2 changes: 1 addition & 1 deletion llama.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -320,7 +320,7 @@ static bool llama_model_load(
uint32_t magic;
fin.read((char *) &magic, sizeof(magic));
if (magic == LLAMA_FILE_MAGIC_UNVERSIONED) {
fprintf(stderr, "%s: invalid model file '%s' (too old, regenerate your model files!)\n",
fprintf(stderr, "%s: invalid model file '%s' (too old, regenerate your model files or convert them with convert-unversioned-ggml-to-ggml.py!)\n",
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this shouldn't be changed, as the conversion script is unsupported.

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I think it's user friendly if it gives a hint to user how to resolve the situation with incompatible model.

__func__, fname.c_str());
return false;
}
Expand Down