Datasets:
metadata
language:
- en
size_categories:
- 10K<n<100K
config_names:
- chat
configs:
- config_name: chat
default: true
data_files:
- split: train
path: data/train.csv
- split: validation
path: data/valid.csv
- split: test
path: data/test.csv
- split: test_geo
path: data/test_geo.csv
- split: test_vis
path: data/test_vis.csv
- split: test_cat
path: data/test_cat.csv
- split: test_web
path: data/test_web.csv
tags:
- conversational
- image-to-text
- vision
- convAI
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
Xing Han Lù, Zdeněk Kasner, Siva Reddy
Quickstart
To get started, simply install datasets
with pip install datasets
and load the chat data splits:
from datasets import load_dataset
# Load the training, validation and test (IID) splits
train = load_dataset("McGill-NLP/weblinx", "train")
valid = load_dataset("McGill-NLP/weblinx", "valid")
test = load_dataset("McGill-NLP/weblinx", "test")
# Load one of the 4 out-of-domain splits (test_web, test_vis, test_geo, test_cat)
test_web = load_dataset("McGill-NLP/weblinx", "test_web")
Raw Data
To use the raw data, you will need to use the huggingface_hub
:
from huggingface_hub import snapshot_download
snapshot_download(repo_id="McGill-NLP/WebLINX-full", repo_type="dataset", local_dir="./data/weblinx")
For more information on how to use this data using our official library, please refer to the WebLINX documentation.