Call us: +256 751 685 275
Study time: Monday - Saturday: 8 AM - 6 PM
Location: 150M from main road, 10 Km from Mityana Town
from transformers import RobertaTokenizer, RobertaTokenizerFast from datasets import load_dataset
In many open-source repositories (such as those found on GitHub), researchers package specific feature sets or pre-processed datasets into compressed files. The likely refers to a specific version or a specific feature subset—perhaps relating to Chapter 136 of WALS, which deals with "M-T Pronouns." When these archives are integrated into an automated pipeline, a "fix" becomes necessary if:
Verdict
If you know block 136 is exactly 512 bytes starting at offset 0x8800 (typical block size), you can split the archive:
def fix_corrupt_zip(input_zip, output_zip): with open(input_zip, 'rb') as f_in: data = f_in.read()
from transformers import RobertaTokenizer, RobertaTokenizerFast from datasets import load_dataset
In many open-source repositories (such as those found on GitHub), researchers package specific feature sets or pre-processed datasets into compressed files. The likely refers to a specific version or a specific feature subset—perhaps relating to Chapter 136 of WALS, which deals with "M-T Pronouns." When these archives are integrated into an automated pipeline, a "fix" becomes necessary if: wals roberta sets 136zip fix
Verdict
If you know block 136 is exactly 512 bytes starting at offset 0x8800 (typical block size), you can split the archive: from transformers import RobertaTokenizer
def fix_corrupt_zip(input_zip, output_zip): with open(input_zip, 'rb') as f_in: data = f_in.read() output_zip): with open(input_zip