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https://nagisawatanabe.com/news/detail/3

公式メンバーシップ『Lighthouse』について

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【速報】岩屋外務大臣宅に不審者侵入　赤坂議員宿舎の警備強化（TBS NEWS DIG Powered by JNN）
https://news.yahoo.co.jp/articles/16f63e59b5dc87004db522fe984b3360563592bc

今買えスレで銘柄出たら即100株買い注文出すプログラム作ったわ

import os
import json
from argparse import ArgumentParser
from glob import glob
from tqdm import tqdm

import torch
from safetensors.torch import load_file, save_file

from kernel import weight_dequant

def main(fp8_path, bf16_path):
torch.set_default_dtype(torch.bfloat16)
os.makedirs(bf16_path, exist_ok=True)
model_index_file = os.path.join(fp8_path, "model.safetensors.index.json")
with open(model_index_file, "r") as f:
model_index = json.load(f)
weight_map = model_index["weight_map"]
fp8_weight_names = []

safetensor_files = list(glob(os.path.join(fp8_path, "*.safetensors")))
for safetensor_file in tqdm(safetensor_files):
file_name = os.path.basename(safetensor_file)
state_dict = load_file(safetensor_file, device="cuda")
new_state_dict = {}
for weight_name, weight in state_dict.items():
if weight_name.endswith("_scale_inv"):
continue
elif weight.element_size() == 1:
scale_inv_name = f"{weight_name}_scale_inv"
assert scale_inv_name in state_dict
fp8_weight_names.append(weight_name)
scale_inv = state_dict[scale_inv_name]
new_state_dict[weight_name] = weight_dequant(weight, scale_inv)
else:
new_state_dict[weight_name] = weight
new_safetensor_file = os.path.join(bf16_path, file_name)
save_file(new_state_dict, new_safetensor_file)

new_model_index_file = os.path.join(bf16_path, "model.safetensors.index.json")
for weight_name in fp8_weight_names:
scale_inv_name = f"{weight_name}_scale_inv"
assert scale_inv_name in weight_map
weight_map.pop(scale_inv_name)
with open(new_model_index_file, "w") as f:
json.dump({"metadata": {}, "weight_map": weight_map}, f, indent=2)

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