| from datasets import load_dataset |
| dataset = load_dataset("allenai/s2orc", |
| split="train[:1%]", |
| num_proc=20) |
| import spacy |
| import spacy_fastlang |
| nlp = spacy.load("en_core_web_sm") |
| nlp.disable_pipes(nlp.pipe_names) |
| nlp.add_pipe("language_detector") |
| def has_abstract(example): |
| |
| if "paperAbstract" in example.keys() and example["paperAbstract"] is not None \ |
| and len(example["paperAbstract"].split())>5: |
| doc = nlp(example["paperAbstract"]) |
| if doc._.language == 'en' and doc._.language_score >= 0.8: |
| return True |
| return False |
| dataset_sub = dataset.filter(has_abstract) |
| dataset_sub.push_to_hub("leminda-ai/s2orc_small",split='train',token='XXXXXXXXXXXX') |
