gender-classification
task318_stereoset_classification_gender
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task318_stereoset_classification_gender
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task318_stereoset_classification_gender.task341_winomt_classification_gender_anti
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task341_winomt_classification_gender_anti
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task341_winomt_classification_gender_anti.task351_winomt_classification_gender_identifiability_anti
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task351_winomt_classification_gender_identifiability_anti
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task351_winomt_classification_gender_identifiability_anti.ViSpeech-Gender-Dialect-Classificationimport datasets as hugDS
import pandas as pd
import os
os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
from df.io import resample
from df.enhance import enhance, init_df
import torch
import warnings
df_model, df_state, _ = init_df()
SAMPLING_RATE = 16_000
def normalize_vietmed(example):
global vietmed_info
example["gender"] = vietmed_info[vietmed_info["Speaker ID"] == example["Speaker ID"]]["Gender"].values[0].lower()
example["dialect"] = vietmed_info[vietmed_info["Speaker ID"] ==… See the full description on the dataset page: https://huggingface.co/datasets/hr16/ViSpeech-Gender-Dialect-Classification.gender-classificationGender_Classification