<jupyter_start><jupyter_text>Download dataset from kaggle<jupyter_code>! pip install -q kaggle
from google.colab import files
files.upload()

 ! mkdir ~/.kaggle
! cp kaggle.json ~/.kaggle/
 ! chmod 600 ~/.kaggle/kaggle.json
!kaggle datasets download -d vaibhao/handwritten-characters
import os
os.chdir('/content/drive/MyDrive/training_colab')<jupyter_output><empty_output><jupyter_text>unzip the data<jupyter_code>import os
import zipfile

local_zip = '/content/handwritten-characters.zip'
zip_ref = zipfile.ZipFile(local_zip, 'r')
zip_ref.extractall('/content')
zip_ref.close()<jupyter_output><empty_output><jupyter_text>Trainining<jupyter_code>!python train.py /content/Train /content/Validation<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12362637362637363, 'fraction_numerical': 0.004120879120879121, 'mean_word_length': 7.379310344827586, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 2, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '105668', 'license': 'MIT', 'n_tokens_mistral': 281, 'n_tokens_neox': 271, 'n_words': 44, 'path': 'TRR & CDI/TRR/colab_training_.ipynb', 'repo_name': 'ProxMaq/ProxVision', 'size': '728'}