goddoe

"""
The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
This file is the complete algorithm.
Everything else is just efficiency.

@karpathy
"""

import os       # os.path.exists
import math     # math.log, math.exp

goddoe

// Claude Code is a Beta product per Anthropic's Commercial Terms of Service.
// By using Claude Code, you agree that all code acceptance or rejection decisions you make,
// and the associated conversations in context, constitute Feedback under Anthropic's Commercial Terms,
// and may be used to improve Anthropic's products, including training models.
// You are responsible for reviewing any code suggestions before use.

// (c) Anthropic PBC. All rights reserved. Use is subject to Anthropic's Commercial Terms of Service (https://www.anthropic.com/legal/commercial-terms).

// Version: 0.2.9

goddoe

You are a powerful agentic AI coding assistant, powered by Claude 3.5 Sonnet. You operate exclusively in Cursor, the world's best IDE.

You are pair programming with a USER to solve their coding task.
The task may require creating a new codebase, modifying or debugging an existing codebase, or simply answering a question.
Each time the USER sends a message, we may automatically attach some information about their current state, such as what files they have open, where their cursor is, recently viewed files, edit history in their session so far, linter errors, and more.
This information may or may not be relevant to the coding task, it is up for you to decide.
Your main goal is to follow the USER's instructions at each message, denoted by the <user_query> tag.

<communication>
1. Be conversational but professional.

goddoe

Begin by enclosing all thoughts within <thinking> tags, exploring multiple angles and approaches.
Break down the solution into clear steps within <step> tags. Start with a 20-step budget, requesting more for complex problems if needed.
Use <count> tags after each step to show the remaining budget. Stop when reaching 0.
Continuously adjust your reasoning based on intermediate results and reflections, adapting your strategy as you progress.
Regularly evaluate progress using <reflection> tags. Be critical and honest about your reasoning process.
Assign a quality score between 0.0 and 1.0 using <reward> tags after each reflection. Use this to guide your approach:

0.8+: Continue current approach
0.5-0.7: Consider minor adjustments
Below 0.5: Seriously consider backtracking and trying a different approach

goddoe

# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software

goddoe

NLU open datatsets

Unstructured

• Reuters (RCV1, RCV2, TRC2)
• Reddit comments
• Wikipedia
• Twitter Stream
• OpenWebText

goddoe

CMake를 왜 쓰는거죠?
좋은 툴은 Visual Studio 뿐입니다. 그 이외에는 전부 사도(邪道)입니다 사도! - 작성자

주의

• 이 문서는 CMake를 주관적으로 서술합니다
• 이 문서를 통해 CMake를 시작하기엔 적합하지 않습니다
  https://cgold.readthedocs.io/en/latest/ 3.1 챕터까지 따라해본 이후 기본사항들을 속성으로 익히는 것을 돕기위한 보조자료로써 작성되었습니다

goddoe

#!/usr/bin/env python
# -*- coding:UTF-8 -*-

import torch
import torch.nn as nn
import torch.nn.init as init


def weight_init(m):
    '''

goddoe

x = torch.randn(10)
print(x)
y, ind = torch.sort(x, 0)
print("y", y)
print("ind", ind)
unsorted = y.new(*y.size())
unsorted.scatter_(0, ind, y)
print("unsorted:", unsorted)
print((x - unsorted).abs().max())

goddoe

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname