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| # train_grpo.py | |
| import re | |
| import torch | |
| from datasets import load_dataset, Dataset | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| from peft import LoraConfig | |
| from trl import GRPOConfig, GRPOTrainer | |
| # Load and prep dataset |
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| // ==UserScript== | |
| // @name Medium Paywall Bypass | |
| // @namespace Violentmonkey Scripts | |
| // @run-at document-start | |
| // @match *://*.medium.com/* | |
| // @match *://medium.com/* | |
| // @match *://*/* | |
| // @grant none | |
| // @version 2.4 | |
| // @inject-into content |
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| import asyncio | |
| import concurrent | |
| from concurrent.futures import ThreadPoolExecutor | |
| from contextlib import contextmanager | |
| import sys | |
| import random | |
| import time | |
| import uvloop | |
| asyncio.set_event_loop_policy(uvloop.EventLoopPolicy()) |
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| #!/bin/bash | |
| ### steps #### | |
| # verify the system has a cuda-capable gpu | |
| # download and install the nvidia cuda toolkit and cudnn | |
| # setup environmental variables | |
| # verify the installation | |
| ### | |
| ### to verify your gpu is cuda enable check |
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