Remove evil parts of answer.
import outlines
qwen_model = outlines.models.transformers("Qwen/Qwen2.5-14B-Instruct", model_kwargs=dict(load_in_8bit=True))
def ask_non_evil_question(prompt, pattern, model=qwen_model, max_tokens=100):
import os | |
import sys | |
with open(sys.argv[0]) as f: | |
code = f.read() # read the code of this file ASAP, for logging | |
with open('optimizer.py', 'r', encoding='utf-8') as f: | |
source_code = f.read() | |
code += source_code | |
with open('model.py', 'r', encoding='utf-8') as f: |
import os | |
import sys | |
with open(sys.argv[0]) as f: | |
code = f.read() # read the code of this file ASAP, for logging | |
import uuid | |
import time | |
import contextlib | |
from dataclasses import dataclass | |
import math | |
from pathlib import Path |
import os | |
import sys | |
with open(sys.argv[0]) as f: | |
code = f.read() # read the code of this file ASAP, for logging | |
import uuid | |
import time | |
import contextlib | |
from dataclasses import dataclass | |
import math | |
from pathlib import Path |
import os | |
import sys | |
with open(sys.argv[0]) as f: | |
code = f.read() # read the code of this file ASAP, for logging | |
import uuid | |
import time | |
import contextlib | |
from dataclasses import dataclass | |
from pathlib import Path |
import os | |
import sys | |
with open(sys.argv[0]) as f: | |
code = f.read() # read the code of this file ASAP, for logging | |
import uuid | |
import glob | |
import time | |
import contextlib | |
from dataclasses import dataclass | |
from typing import Optional |
Running pytorch 2.6.0.dev20241126+cu124 compiled for CUDA 12.4 | |
nvidia-smi: | |
Fri Nov 29 00:54:16 2024 | |
+-----------------------------------------------------------------------------------------+ | |
| NVIDIA-SMI 550.76 Driver Version: 550.76 CUDA Version: 12.4 | | |
|-----------------------------------------+------------------------+----------------------+ | |
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | |
| | | MIG M. | | |
|=========================================+========================+======================| |
import random | |
import collections | |
def trial(first_to=2): | |
flips = [random.choice([True, False]) for _ in range(100)] | |
alice_flip_checks = flips | |
bob_flip_checks = [flips[i] for i in range(1, len(flips), 2)] + [flips[i] for i in range(0, len(flips), 2)] | |
# get second_head | |
try: |
from datasets import Dataset, load_from_disk | |
from transformers import TrainingArguments | |
from transformers.trainer_utils import EvalLoopOutput | |
from unsloth import FastLanguageModel | |
import random | |
from huggingface_hub import create_repo | |
from scipy.spatial.distance import cosine | |
from sentence_transformers import SentenceTransformer | |
import statistics |
# Huge Pattern | |
`0(0(0([1235679]-(0(2-(0[1-9]|1\\d|2[0-8])|[13578]-(0[1-9]|3[01]|[12]\\d)|[469]-(0[1-9]|30|[12]\\d))|1(1-(0[1-9]|30|[12]\\d)|[02]-(0[1-9]|3[01]|[12]\\d)))|[48]-(0(2-(0[1-9]|[12]\\d)|[13578]-(0[1-9]|3[01]|[12]\\d)|[469]-(0[1-9]|30|[12]\\d))|1(1-(0[1-9]|30|[12]\\d)|[02]-(0[1-9]|3[01]|[12]\\d))))|[13579]([01345789]-(0(2-(0[1-9]|1\\d|2[0-8])|[13578]-(0[1-9]|3[01]|[12]\\d)|[469]-(0[1-9]|30|[12]\\d))|1(1-(0[1-9]|30|[12]\\d)|[02]-(0[1-9]|3[01]|[12]\\d)))|[26]-(0(2-(0[1-9]|[12]\\d)|[13578]-(0[1-9]|3[01]|[12]\\d)|[469]-(0[1-9]|30|[12]\\d))|1(1-(0[1-9]|30|[12]\\d)|[02]-(0[1-9]|3[01]|[12]\\d))))|[2468]([048]-(0(2-(0[1-9]|[12]\\d)|[13578]-(0[1-9]|3[01]|[12]\\d)|[469]-(0[1-9]|30|[12]\\d))|1(1-(0[1-9]|30|[12]\\d)|[02]-(0[1-9]|3[01]|[12]\\d)))|[1235679]-(0(2-(0[1-9]|1\\d|2[0-8])|[13578]-(0[1-9]|3[01]|[12]\\d)|[469]-(0[1-9]|30|[12]\\d))|1(1-(0[1-9]|30|[12]\\d)|[02]-(0[1-9]|3[01]|[12]\\d)))))|[1235679](0([0-35679]-(0(2-(0[1-9]|1\\d|2[0-8])|[13578]-(0[1-9]|3[01]|[12]\\d)|[469]-(0[1-9]|30|[12]\\d))|1(1-(0[1-9]|30 |