Develop an AI prompt that solves random 12-token instances of the A::B problem (defined here), with 90%+ success rate.
We'll use your prompt as the SYSTEM PROMPT, and a specific instance of problem as the PROMPT, inside XML tags. Example:
| // I'm tired of extensions that automatically: | |
| // - show welcome pages / walkthroughs | |
| // - show release notes | |
| // - send telemetry | |
| // - recommend things | |
| // | |
| // This disables all of that stuff. | |
| // If you have more config, leave a comment so I can add it!! | |
| { |
Develop an AI prompt that solves random 12-token instances of the A::B problem (defined here), with 90%+ success rate.
We'll use your prompt as the SYSTEM PROMPT, and a specific instance of problem as the PROMPT, inside XML tags. Example:
| from datasets import load_dataset | |
| from sentence_transformers import ( | |
| SentenceTransformerTrainer, | |
| SentenceTransformerTrainingArguments, | |
| ) | |
| from pylate import losses, models, utils | |
| def main(): | |
| # As ReasonIR do not re-upload the BRIGHT data, we need to load it from the original source |
| #!/usr/bin/env python3 | |
| import torch, gymnasium as gym, numpy as np, time, sys, threading, os, random | |
| import torch.multiprocessing as mp | |
| from torch import Tensor | |
| from bg_record import log_step, bind_logger, log_close | |
| # torch.set_num_threads(1) | |
| NUM_PROCS = 16 |