bidirectional
bidirectional-lstm-imdbmedical-bidirectional-machine-translationmedical-bidirectional-machine-translation-checkpoints-340694MT_Nuer_to_English_BidirectionalHY-WorldPlay-Bidirectional-Diffusersnllb-finetuned-sw-ki-bidirectionalstepaudio2-mini-luganda-english-bidirectional-s2st-fullSANA-WM_bidirectional-stage1-diffusers
kulyk-bidirectionalscissor_bidirectional_160This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "so_follower",
"total_episodes": 4,
"total_frames": 1030,
"total_tasks": 2,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 30,
"splits": {
"train": "0:4"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/miladgholami/scissor_bidirectional_160.kulyk-bidirectional-gemmakurdish-bidirectional-translation-v2pristine-twi-english-bidirectional-multilen
This dataset is shared under CC BY-NC 4.0, which means you are free to use, share, and adapt it for non-commercial research and educational purposes with attribution. You can read the full license at https://creativecommons.org/licenses/by-nc/4.0/.
Twi ↔ English Bidirectional MT Dataset
Derived from ghananlpcommunity/pristine-twi-english.
Schema
Field
Type
Description
source
string
Source text (no prefix token)
target
string
Clean target translation… See the full description on the dataset page: https://huggingface.co/datasets/ghananlpcommunity/pristine-twi-english-bidirectional-multilen.mtet-vi-en-bidirectional
MTET Vietnamese–English Bidirectional Dataset (Cleaned)
This is the cleaned, bidirectional version of the MTET (Machine Translation Evaluation for Translation) Vietnamese–English parallel corpus used to train the vi-en-transformer-25m model.
Files
File
Description
mtet_bidirectional_cleaned.csv
Main training data (bidirectional, cleaned)
Usage
import pandas as pd
df = pd.read_csv("mtet_bidirectional_cleaned.csv")
print(df.head())
# source… See the full description on the dataset page: https://huggingface.co/datasets/Cong123779/mtet-vi-en-bidirectional.