mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2025-10-30 08:42:00 +00:00
137 lines
3.7 KiB
Python
137 lines
3.7 KiB
Python
# Convert a LLaMA model checkpoint to a ggml compatible file
|
|
#
|
|
# Load the model using Torch
|
|
# Iterate over all variables and write them to a binary file.
|
|
#
|
|
# For each variable, write the following:
|
|
# - Number of dimensions (int)
|
|
# - Name length (int)
|
|
# - Dimensions (int[n_dims])
|
|
# - Name (char[name_length])
|
|
# - Data (float[n_dims])
|
|
#
|
|
# By default, the bigger matrices are converted to 16-bit floats.
|
|
# This can be disabled by adding the "use-f32" CLI argument.
|
|
#
|
|
# At the start of the ggml file we write the model parameters
|
|
# and vocabulary.
|
|
#
|
|
|
|
import sys
|
|
import json
|
|
import struct
|
|
import numpy as np
|
|
import torch
|
|
|
|
from sentencepiece import SentencePieceProcessor
|
|
|
|
if len(sys.argv) < 3:
|
|
print("Usage: convert-ckpt-to-ggml.py dir-model ftype\n")
|
|
print(" ftype == 0 -> float32")
|
|
print(" ftype == 1 -> float16")
|
|
sys.exit(1)
|
|
|
|
# output in the same directory as the model
|
|
dir_model = sys.argv[1]
|
|
fname_out = sys.argv[1] + "/ggml-model.bin"
|
|
|
|
fname_hparams = sys.argv[1] + "/params.json"
|
|
fname_model = sys.argv[1] + "/consolidated.00.pth"
|
|
fname_tokenizer = sys.argv[1] + "/../tokenizer.model"
|
|
|
|
# possible data types
|
|
# ftype == 0 -> float32
|
|
# ftype == 1 -> float16
|
|
#
|
|
# map from ftype to string
|
|
ftype_str = ["f32", "f16"]
|
|
|
|
ftype = 1
|
|
if len(sys.argv) > 2:
|
|
ftype = int(sys.argv[2])
|
|
if ftype < 0 or ftype > 1:
|
|
print("Invalid ftype: " + str(ftype))
|
|
sys.exit(1)
|
|
fname_out = sys.argv[1] + "/ggml-model-" + ftype_str[ftype] + ".bin"
|
|
|
|
with open(fname_hparams, "r") as f:
|
|
hparams = json.load(f)
|
|
|
|
tokenizer = SentencePieceProcessor(fname_tokenizer)
|
|
|
|
hparams.update({"vocab_size": tokenizer.vocab_size()})
|
|
|
|
print(hparams)
|
|
|
|
model = torch.load(fname_model, map_location="cpu")
|
|
|
|
fout = open(fname_out, "wb")
|
|
|
|
fout.write(struct.pack("i", 0x67676d6c)) # magic: ggml in hex
|
|
fout.write(struct.pack("i", hparams["vocab_size"]))
|
|
fout.write(struct.pack("i", hparams["dim"]))
|
|
fout.write(struct.pack("i", hparams["multiple_of"]))
|
|
fout.write(struct.pack("i", hparams["n_heads"]))
|
|
fout.write(struct.pack("i", hparams["n_layers"]))
|
|
fout.write(struct.pack("i", 64)) # rot
|
|
fout.write(struct.pack("i", ftype))
|
|
|
|
# Is this correct??
|
|
for i in range(32000):
|
|
# TODO: this is probably wrong - not sure how this tokenizer works
|
|
text = tokenizer.decode([29889, i]).encode('utf-8')
|
|
# remove the first byte (it's always '.')
|
|
text = text[1:]
|
|
fout.write(struct.pack("i", len(text)))
|
|
fout.write(text)
|
|
|
|
for k, v in model.items():
|
|
name = k
|
|
shape = v.shape
|
|
|
|
# skip layers.X.attention.inner_attention.rope.freqs
|
|
if name[-5:] == "freqs":
|
|
continue
|
|
|
|
print("Processing variable: " + name + " with shape: ", shape, " and type: ", v.dtype)
|
|
|
|
#data = tf.train.load_variable(dir_model, name).squeeze()
|
|
data = v.numpy().squeeze()
|
|
n_dims = len(data.shape);
|
|
|
|
# for efficiency - transpose some matrices
|
|
# "model/h.*/attn/c_attn/w"
|
|
# "model/h.*/attn/c_proj/w"
|
|
# "model/h.*/mlp/c_fc/w"
|
|
# "model/h.*/mlp/c_proj/w"
|
|
#if name[-14:] == "/attn/c_attn/w" or \
|
|
# name[-14:] == "/attn/c_proj/w" or \
|
|
# name[-11:] == "/mlp/c_fc/w" or \
|
|
# name[-13:] == "/mlp/c_proj/w":
|
|
# print(" Transposing")
|
|
# data = data.transpose()
|
|
|
|
dshape = data.shape
|
|
|
|
# default type is fp16
|
|
ftype_cur = 1
|
|
if ftype == 0 or n_dims == 1:
|
|
print(" Converting to float32")
|
|
data = data.astype(np.float32)
|
|
ftype_cur = 0
|
|
|
|
# header
|
|
str = name.encode('utf-8')
|
|
fout.write(struct.pack("iii", n_dims, len(str), ftype_cur))
|
|
for i in range(n_dims):
|
|
fout.write(struct.pack("i", dshape[n_dims - 1 - i]))
|
|
fout.write(str);
|
|
|
|
# data
|
|
data.tofile(fout)
|
|
|
|
fout.close()
|
|
|
|
print("Done. Output file: " + fname_out)
|
|
print("")
|