| # Print iterations progress | |
| # from: https://gist.github.com/aubricus/f91fb55dc6ba5557fbab06119420dd6a | |
| def print_progress(iteration, total, prefix="", suffix="", decimals=1, bar_length=100): | |
| """Call in a loop to create terminal progress bar. | |
| @params: | |
| iteration - Required : current iteration (Int) | |
| total - Required : total iterations (Int) | |
| prefix - Optional : prefix string (Str) |
| from textwrap import fill | |
| text = 30 * "Hello world! " | |
| print(fill(text, width=80)) |
| root = true | |
| [*] | |
| charset = utf-8 | |
| end_of_line = lf | |
| indent_size = 4 | |
| indent_style = space | |
| insert_final_newline = true | |
| max_line_length = 120 | |
| tab_width = 4 |
This README will guide you through the process of installing packages directly from a Git repository in a way that is compatible with both Google Colab and Jupyter Notebooks. The provided code will attempt to execute compatible commands depending on the running environment.
%load_ext autoreload
| # gist for the blog post on https://safjan.com | |
| import tiktoken | |
| import math | |
| # Exemplary text | |
| text = "Another vital aspect to consider in the realm of text generation is perplexity. Essentially, perplexity refers to the amount of information contained within a text. Natural language possesses a remarkable redundancy that enables effective communication, even in noisy environments such as a crowded bar or an intimate dinner. This redundancy allows for the overall message to be comprehended, even if certain parts of the text are missing or obscured." | |
| # Tokenize the text using tiktoken | |
| tokens = tiktoken.tokenize(text) |
A script to call the Azure OpenAI API and ask a question, returning the answer.
ask_gpt.sh is a Bash script that interacts with the Azure OpenAI API to ask a question and retrieve the corresponding answer. It simplifies the process of making API calls and handling the JSON response.
A Python script for splitting text into parts with controlled (limited) length in tokens. This script utilizes the tiktoken library for encoding and decoding text.
| """ | |
| Skrypt obliczający odsetki ustawowe od należności podanych w pliku csv | |
| Przykladowa zawartość pliku: | |
| required_payment_date,payment_amount | |
| 2023-02-10,2700 | |
| 2023-03-10,1200 | |
| """ |
c- to kolor tła
| import numpy as np | |
| from sklearn.manifold import TSNE | |
| from plotly import graph_objs as go | |
| # generate 10-dimensional data | |
| X = np.random.rand(100, 10) | |
| print(X.shape) | |
| # reduce to 3 components | |
| X_embedded = TSNE(n_components=3).fit_transform(X) |