mirror of
https://github.com/osmarks/nanogpt-experiments.git
synced 2024-11-11 04:19:57 +00:00
33 lines
1013 B
Python
33 lines
1013 B
Python
import os
|
|
import requests
|
|
import tiktoken
|
|
import numpy as np
|
|
|
|
# download the tiny shakespeare dataset
|
|
if not os.path.exists('input.txt'):
|
|
data_url = 'https://raw.githubusercontent.com/karpathy/char-rnn/master/data/tinyshakespeare/input.txt'
|
|
with open('input.txt', 'w') as f:
|
|
f.write(requests.get(data_url).text)
|
|
|
|
with open('input.txt', 'r') as f:
|
|
data = f.read()
|
|
n = len(data)
|
|
train_data = data[:int(n*0.9)]
|
|
val_data = data[int(n*0.9):]
|
|
|
|
# encode with tiktoken gpt2 bpe
|
|
enc = tiktoken.get_encoding("gpt2")
|
|
train_ids = enc.encode_ordinary(train_data)
|
|
val_ids = enc.encode_ordinary(val_data)
|
|
print(f"train has {len(train_ids):,} tokens")
|
|
print(f"val has {len(val_ids):,} tokens")
|
|
|
|
# export to bin files
|
|
train_ids = np.array(train_ids, dtype=np.uint16)
|
|
val_ids = np.array(val_ids, dtype=np.uint16)
|
|
train_ids.tofile(os.path.join(os.path.dirname(__file__), 'train.bin'))
|
|
val_ids.tofile(os.path.join(os.path.dirname(__file__), 'val.bin'))
|
|
|
|
# train.bin has 301,966 tokens
|
|
# val.bin has 36,059 tokens
|