#jupyter_notebook#ai#artificial_intelligence#chatgpt#deep_learning#from_scratch#gpt#language_model#large_language_models#llm#machine_learning#python#pytorch#transformer
You can learn how to build your own large language model (LLM) like GPT from scratch with clear, step-by-step guidance, including coding, training, and fine-tuning, all explained with examples and diagrams. This approach mirrors how big models like ChatGPT are made but is designed to run on a regular laptop without special hardware. You also get access to code for loading pretrained models and fine-tuning them for tasks like text classification or instruction following. This helps you deeply understand how LLMs work inside and lets you create your own functional AI assistant, gaining practical skills in AI development[1][2][3][4].
https://github.com/rasbt/LLMs-from-scratch
# The standard string repr for dicts is hard to read:
»> my_mapping = {'a': 23, 'b': 42, 'c': 0xc0ffee}
»> my_mapping
{'b': 42, 'c': 12648430. 'a': 23} # 😞
# The "#json" module can do a much better job:
»> import json
»> print(json.dumps(my_mapping, indent=4, sort_keys=True))
{
"a": 23,
"b": 42,
"c": 12648430
}
# Note this only works with dicts containing
# primitive types (check out the "pprint" module):
»> json.dumps({all: 'yup'})
TypeError: keys must be a string
История(12м) как в Альфа-Банке сокращали размер JSON файла, который передается на устройство для работы SDUI. Решением стала шаблонизация для отказа от одинаковых блоков UI с разными данными
#оптимизация#json
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