Datasets:
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Update parquet files
Browse files- .gitattributes +8 -0
- README.md +0 -258
- dataset_infos.json +0 -1
- dummy/mmchat/1.0.0/dummy_data.zip +0 -0
- dummy/mmchat/1.0.0/dummy_data.zip.lock +0 -0
- dummy/mmchat_hf/1.0.0/dummy_data.zip +0 -0
- dummy/mmchat_hf/1.0.0/dummy_data.zip.lock +0 -0
- dummy/mmchat_lccc_filtered/1.0.0/dummy_data.zip +0 -0
- dummy/mmchat_lccc_filtered/1.0.0/dummy_data.zip.lock +0 -0
- dummy/mmchat_raw/1.0.0/dummy_data.zip +0 -0
- dummy/mmchat_raw/1.0.0/dummy_data.zip.lock +0 -0
- mmchat.py +0 -231
- mmchat/img_url_test.jsonl.gz +0 -3
- mmchat/img_url_train.jsonl.gz +0 -3
- mmchat/mmchat-test.parquet +0 -0
- mmchat/{dialog_test.jsonl.gz → mmchat-train.parquet} +2 -2
- mmchat/mmchat-validation.parquet +0 -0
- mmchat/weibo_dev.jsonl.gz +0 -3
- mmchat/weibo_test.jsonl.gz +0 -3
- mmchat/weibo_train.jsonl.gz +0 -3
- mmchat_hf/dialog.jsonl.gz +0 -3
- mmchat_hf/human_annotation.jsonl.gz +0 -3
- mmchat/dialog_train.jsonl.gz → mmchat_hf/mmchat-train.parquet +2 -2
- mmchat_hf/weibo.jsonl.gz +0 -3
- mmchat_hf/weibo_img_expanded_url.jsonl.gz +0 -3
- mmchat_lccc_filtered/dialog_lccc_flt.jsonl.gz +0 -3
- mmchat/img_url_dev.jsonl.gz → mmchat_lccc_filtered/mmchat-train.parquet +2 -2
- mmchat_lccc_filtered/weibo_img_expanded_url_lccc_flt.jsonl.gz +0 -3
- mmchat_lccc_filtered/weibo_lccc_flt.jsonl.gz +0 -3
- mmchat_raw/dialog_raw.jsonl.gz +0 -3
- mmchat_raw/mmchat-train-00000-of-00005.parquet +3 -0
- mmchat_raw/mmchat-train-00001-of-00005.parquet +3 -0
- mmchat_raw/mmchat-train-00002-of-00005.parquet +3 -0
- mmchat_raw/mmchat-train-00003-of-00005.parquet +3 -0
- mmchat/dialog_dev.jsonl.gz → mmchat_raw/mmchat-train-00004-of-00005.parquet +2 -2
- mmchat_raw/weibo_img_expanded_url_raw.jsonl.gz +0 -3
- mmchat_raw/weibo_raw.jsonl.gz +0 -3
.gitattributes
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mmchat_lccc_filtered/dialog_lccc_flt.jsonl.gz filter=lfs diff=lfs merge=lfs -text
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mmchat_lccc_filtered/weibo_img_expanded_url_lccc_flt.jsonl.gz filter=lfs diff=lfs merge=lfs -text
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mmchat_lccc_filtered/weibo_lccc_flt.jsonl.gz filter=lfs diff=lfs merge=lfs -text
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mmchat_lccc_filtered/dialog_lccc_flt.jsonl.gz filter=lfs diff=lfs merge=lfs -text
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mmchat_lccc_filtered/weibo_img_expanded_url_lccc_flt.jsonl.gz filter=lfs diff=lfs merge=lfs -text
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mmchat_lccc_filtered/weibo_lccc_flt.jsonl.gz filter=lfs diff=lfs merge=lfs -text
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mmchat/mmchat-train.parquet filter=lfs diff=lfs merge=lfs -text
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mmchat_hf/mmchat-train.parquet filter=lfs diff=lfs merge=lfs -text
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mmchat_lccc_filtered/mmchat-train.parquet filter=lfs diff=lfs merge=lfs -text
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mmchat_raw/mmchat-train-00001-of-00005.parquet filter=lfs diff=lfs merge=lfs -text
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mmchat_raw/mmchat-train-00003-of-00005.parquet filter=lfs diff=lfs merge=lfs -text
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mmchat_raw/mmchat-train-00004-of-00005.parquet filter=lfs diff=lfs merge=lfs -text
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mmchat_raw/mmchat-train-00002-of-00005.parquet filter=lfs diff=lfs merge=lfs -text
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mmchat_raw/mmchat-train-00000-of-00005.parquet filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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annotations_creators:
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- no-annotation
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language_creators:
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- found
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language:
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- zh
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license:
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- other
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multilinguality:
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- monolingual
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paperswithcode_id: mmchat-multi-modal-chat-dataset-on-social
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pretty_name: "MMChat: Multi-Modal Chat Dataset on Social Media"
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size_categories:
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- 10M<n<100M
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source_datasets:
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- original
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task_categories:
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- conversational
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task_ids:
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- dialogue-generation
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---
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# Dataset Card for MMChat
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## Table of Contents
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- [Dataset Card for MMChat](#dataset-card-for-mmchat)
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- [Table of Contents](#table-of-contents)
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits](#data-splits)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
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- [Who are the source language producers?](#who-are-the-source-language-producers)
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- [Annotations](#annotations)
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- [Annotation process](#annotation-process)
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- [Who are the annotators?](#who-are-the-annotators)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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- **Homepage:** https://www.zhengyinhe.com/datasets/
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- **Repository:** https://github.com/silverriver/MMChat
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- **Paper:** https://arxiv.org/abs/2108.07154
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### Dataset Summary
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MMChat is a large-scale dialogue dataset that contains image-grounded dialogues in Chinese. Each dialogue in MMChat is associated with one or more images (maximum 9 images per dialogue). We design various strategies to ensure the quality of the dialogues in MMChat.
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MMChat comes with 4 different versions:
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- `mmchat`: The MMChat dataset used in our paper.
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- `mmchat_hf`: Contains human annotation on 100K sessions of dialogues.
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- `mmchat_raw`: Raw dialogues used to construct MMChat.
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`mmchat_lccc_filtered`: Raw dialogues filtered using the LCCC dataset.
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If you what to use high quality multi-modal dialogues that are closed related to the given images, I suggest you to use the `mmchat_hf` version.
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If you only care about the quality of dialogue texts, I suggest you to use the `mmchat_lccc_filtered` version.
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### Supported Tasks and Leaderboards
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- dialogue-generation: The dataset can be used to train a model for generating dialogue responses.
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- response-retrieval: The dataset can be used to train a reranker model that can be used to implement a retrieval-based dialogue model.
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### Languages
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MMChat is in Chinese
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MMChat中的对话是中文的
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## Dataset Structure
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### Data Instances
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Several versions of MMChat are available. For `mmchat`, `mmchat_raw`, `mmchat_lccc_filtered`, the following instance applies:
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```json
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{
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"dialog": ["你只拍出了你十分之一的美", "你的头像竟然换了,奥"],
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"weibo_content": "分享图片",
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"imgs": ["https://wx4.sinaimg.cn/mw2048/d716a6e2ly1fmug2w2l9qj21o02yox6p.jpg"]
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}
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```
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For `mmchat_hf`, the following instance applies:
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```json
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{
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"dialog": ["白百合", "啊?", "有点像", "还好吧哈哈哈牙像", "有男盆友没呢", "还没", "和你说话呢。没回我"],
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"weibo_content": "补一张昨天礼仪的照片",
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"imgs": ["https://ww2.sinaimg.cn/mw2048/005Co9wdjw1eyoz7ib9n5j307w0bu3z5.jpg"],
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"labels": {
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"image_qualified": true,
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"dialog_qualified": true,
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"dialog_image_related": true
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}
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}
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```
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### Data Fields
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- `dialog` (list of strings): List of utterances consisting of a dialogue.
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- `weibo_content` (string): Weibo content of the dialogue.
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- `imgs` (list of strings): List of URLs of images.
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- `labels` (dict): Human-annotated labels of the dialogue.
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- `image_qualified` (bool): Whether the image is of high quality.
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- `dialog_qualified` (bool): Whether the dialogue is of high quality.
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- `dialog_image_related` (bool): Whether the dialogue is related to the image.
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### Data Splits
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For `mmchat`, we provide the following splits:
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|train|valid|test|
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|---:|---:|---:|
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|115,842 | 4,000 | 1,000 |
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For other versions, we do not provide the offical split.
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More stastics are listed here:
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| `mmchat` | Count |
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|--------------------------------------|--------:|
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| Sessions | 120.84 K |
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| Sessions with more than 4 utterances | 17.32 K |
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| Utterances | 314.13 K |
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| Images | 198.82 K |
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| Avg. utterance per session | 2.599 |
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| Avg. image per session | 2.791 |
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| Avg. character per utterance | 8.521 |
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| `mmchat_hf` | Count |
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|--------------------------------------|--------:|
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| Sessions | 19.90 K |
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| Sessions with more than 4 utterances | 8.91 K |
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| Totally annotated sessions | 100.01 K |
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| Utterances | 81.06 K |
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| Images | 52.66K |
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| Avg. utterance per session | 4.07 |
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| Avg. image per session | 2.70 |
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| Avg. character per utterance | 11.93 |
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| `mmchat_raw` | Count |
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|--------------------------------------|---------:|
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| Sessions | 4.257 M |
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| Sessions with more than 4 utterances | 2.304 M |
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| Utterances | 18.590 M |
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| Images | 4.874 M |
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| Avg. utterance per session | 4.367 |
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| Avg. image per session | 1.670 |
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| Avg. character per utterance | 14.104 |
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| `mmchat_lccc_filtered` | Count |
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|--------------------------------------|--------:|
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| Sessions | 492.6 K |
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| Sessions with more than 4 utterances | 208.8 K |
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| Utterances | 1.986 M |
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| Images | 1.066 M |
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| Avg. utterance per session | 4.031 |
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| Avg. image per session | 2.514 |
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| Avg. character per utterance | 11.336 |
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## Dataset Creation
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### Curation Rationale
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[Needs More Information]
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### Source Data
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#### Initial Data Collection and Normalization
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[Needs More Information]
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#### Who are the source language producers?
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[Needs More Information]
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### Annotations
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#### Annotation process
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[Needs More Information]
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#### Who are the annotators?
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[Needs More Information]
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### Personal and Sensitive Information
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[Needs More Information]
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## Considerations for Using the Data
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### Social Impact of Dataset
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[Needs More Information]
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### Discussion of Biases
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[Needs More Information]
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### Other Known Limitations
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[Needs More Information]
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## Additional Information
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### Dataset Curators
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[Needs More Information]
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### Licensing Information
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other-weibo
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This dataset is collected from Weibo.
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You can refer to the [detailed policy](https://weibo.com/signup/v5/privacy) required to use this dataset.
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Please restrict the usage of this dataset to non-commerical purposes.
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### Citation Information
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```
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@inproceedings{zheng2022MMChat,
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author = {Zheng, Yinhe and Chen, Guanyi and Liu, Xin and Sun, Jian},
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title = {MMChat: Multi-Modal Chat Dataset on Social Media},
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booktitle = {Proceedings of The 13th Language Resources and Evaluation Conference},
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year = {2022},
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publisher = {European Language Resources Association},
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}
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@inproceedings{wang2020chinese,
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title={A Large-Scale Chinese Short-Text Conversation Dataset},
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author={Wang, Yida and Ke, Pei and Zheng, Yinhe and Huang, Kaili and Jiang, Yong and Zhu, Xiaoyan and Huang, Minlie},
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booktitle={NLPCC},
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year={2020},
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url={https://arxiv.org/abs/2008.03946}
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}
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```
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### Contributions
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Thanks to [Yinhe Zheng](https://github.com/silverriver) for adding this dataset.
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{"mmchat": {"description": "MMChat is a large-scale dialogue dataset that contains image-grounded dialogues in Chinese.\nEach dialogue in MMChat is associated with one or more images (maximum 9 images per dialogue).\nWe design various strategies to ensure the quality of the dialogues in MMChat.\n", "citation": "@inproceedings{zheng2022MMChat,\nauthor = {Zheng, Yinhe and Chen, Guanyi and Liu, Xin and Sun, Jian},\ntitle = {MMChat: Multi-Modal Chat Dataset on Social Media},\nbooktitle = {Proceedings of The 13th Language Resources and Evaluation Conference},\nyear = {2022},\npublisher = {European Language Resources Association},\n}\n\n@inproceedings{wang2020chinese,\n title = {A Large-Scale Chinese Short-Text Conversation Dataset},\n author = {Wang, Yida and Ke, Pei and Zheng, Yinhe and Huang, Kaili and Jiang, Yong and Zhu, Xiaoyan and Huang, Minlie},\n booktitle = {NLPCC},\n year = {2020},\n url = {https://arxiv.org/abs/2008.03946}\n}\n", "homepage": "https://github.com/silverriver/MMChat", "license": "MIT", "features": {"dialog": [{"dtype": "string", "id": null, "_type": "Value"}], "weibo_content": {"dtype": "string", "id": null, "_type": "Value"}, "imgs": [{"dtype": "string", "id": null, "_type": "Value"}]}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "mmchat", "config_name": "mmchat", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 35036683, "num_examples": 115842, "dataset_name": "mmchat"}, "test": {"name": "test", "num_bytes": 1242236, "num_examples": 4000, "dataset_name": "mmchat"}, "validation": {"name": "validation", "num_bytes": 305657, "num_examples": 1000, "dataset_name": "mmchat"}}, "download_checksums": {"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat/dialog_train.jsonl.gz": {"num_bytes": 4001249, "checksum": 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"7f6cef2b570a3aa187d823ab5330806e79f9dd66e4ade4cae78ef7815764d2ee"}, "https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat/dialog_test.jsonl.gz": {"num_bytes": 141556, "checksum": "f285407f893abc385588160a674c6ad846bce93f0a821acf093bcd8a8d40e685"}, "https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat/img_url_test.jsonl.gz": {"num_bytes": 188377, "checksum": "9db4713683a665764085e7480165a7f7c038b2c6239d1c744976298363a5579e"}, "https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat/weibo_test.jsonl.gz": {"num_bytes": 189, "checksum": "3eaabda17b2e4df3985f6f302f2581ed818a03ae04cc7112f7feb1fcddc4c47b"}}, "download_size": 9718929, "post_processing_size": null, "dataset_size": 36584576, "size_in_bytes": 46303505}, "mmchat_hf": {"description": "MMChat is a large-scale dialogue dataset that contains image-grounded dialogues in Chinese.\nEach dialogue in MMChat is associated with one or more images (maximum 9 images per dialogue).\nWe design various strategies to ensure the quality of the dialogues in MMChat.\n", "citation": "@inproceedings{zheng2022MMChat,\nauthor = {Zheng, Yinhe and Chen, Guanyi and Liu, Xin and Sun, Jian},\ntitle = {MMChat: Multi-Modal Chat Dataset on Social Media},\nbooktitle = {Proceedings of The 13th Language Resources and Evaluation Conference},\nyear = {2022},\npublisher = {European Language Resources Association},\n}\n\n@inproceedings{wang2020chinese,\n title = {A Large-Scale Chinese Short-Text Conversation Dataset},\n author = {Wang, Yida and Ke, Pei and Zheng, Yinhe and Huang, Kaili and Jiang, Yong and Zhu, Xiaoyan and Huang, Minlie},\n booktitle = {NLPCC},\n year = {2020},\n url = {https://arxiv.org/abs/2008.03946}\n}\n", "homepage": "https://github.com/silverriver/MMChat", "license": "MIT", "features": {"dialog": [{"dtype": "string", "id": null, "_type": "Value"}], "weibo_content": {"dtype": "string", "id": null, "_type": "Value"}, "imgs": [{"dtype": "string", "id": null, "_type": "Value"}], "labels": {"image_qualified": {"dtype": "bool", "id": null, "_type": "Value"}, "dialog_qualified": {"dtype": "bool", "id": null, "_type": "Value"}, "dialog_image_related": {"dtype": "bool", "id": null, "_type": "Value"}}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "mmchat", "config_name": "mmchat_hf", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 47268457, "num_examples": 100011, "dataset_name": "mmchat"}}, "download_checksums": {"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_hf/dialog.jsonl.gz": {"num_bytes": 6826130, "checksum": "15fcf7756ec5ca39398a4ab9d68d14c403b1f4273781130f90dacb55a862c58a"}, "https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_hf/weibo_img_expanded_url.jsonl.gz": {"num_bytes": 7781846, "checksum": "58fccfe34603c92dcb435dde7f7f77f7468dba2df369a412a927d65041f18724"}, "https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_hf/weibo.jsonl.gz": {"num_bytes": 7084046, "checksum": "4031029e1abbdca3fa71755796a52f8f6788ae77390f2b7107822b8eb792bcb0"}, "https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_hf/human_annotation.jsonl.gz": {"num_bytes": 358333, "checksum": "6d34e113027e86f44af220c2c9ce09f909aaff045cd94fd5886b79a972b6e0b4"}}, "download_size": 22050355, "post_processing_size": null, "dataset_size": 47268457, "size_in_bytes": 69318812}, "mmchat_raw": {"description": "MMChat is a large-scale dialogue dataset that contains image-grounded dialogues in Chinese.\nEach dialogue in MMChat is associated with one or more images (maximum 9 images per dialogue).\nWe design various strategies to ensure the quality of the dialogues in MMChat.\n", "citation": "@inproceedings{zheng2022MMChat,\nauthor = {Zheng, Yinhe and Chen, Guanyi and Liu, Xin and Sun, Jian},\ntitle = {MMChat: Multi-Modal Chat Dataset on Social Media},\nbooktitle = {Proceedings of The 13th Language Resources and Evaluation Conference},\nyear = {2022},\npublisher = {European Language Resources Association},\n}\n\n@inproceedings{wang2020chinese,\n title = {A Large-Scale Chinese Short-Text Conversation Dataset},\n author = {Wang, Yida and Ke, Pei and Zheng, Yinhe and Huang, Kaili and Jiang, Yong and Zhu, Xiaoyan and Huang, Minlie},\n booktitle = {NLPCC},\n year = {2020},\n url = {https://arxiv.org/abs/2008.03946}\n}\n", "homepage": "https://github.com/silverriver/MMChat", "license": "MIT", "features": {"dialog": [{"dtype": "string", "id": null, "_type": "Value"}], "weibo_content": {"dtype": "string", "id": null, "_type": "Value"}, "imgs": [{"dtype": "string", "id": null, "_type": "Value"}]}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "mmchat", "config_name": "mmchat_raw", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2012399665, "num_examples": 4256871, "dataset_name": "mmchat"}}, "download_checksums": {"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_raw/dialog_raw.jsonl.gz": {"num_bytes": 389104370, "checksum": "8d36cd302c42eee9a9d39032ff0e1d05975bd5aa2030eecd595e2e2964f6cadf"}, "https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_raw/weibo_img_expanded_url_raw.jsonl.gz": {"num_bytes": 268962111, "checksum": "d0deae3fe9b2bced80ba424fa9110a4e52b583f5823723832ac628e943e0a228"}, "https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_raw/weibo_raw.jsonl.gz": {"num_bytes": 329066732, "checksum": "d2616195f89040a0cb81d16261293f9ff002d2eb7981eebde2f631069f202521"}}, "download_size": 987133213, "post_processing_size": null, "dataset_size": 2012399665, "size_in_bytes": 2999532878}, "mmchat_lccc_filtered": {"description": "MMChat is a large-scale dialogue dataset that contains image-grounded dialogues in Chinese.\nEach dialogue in MMChat is associated with one or more images (maximum 9 images per dialogue).\nWe design various strategies to ensure the quality of the dialogues in MMChat.\n", "citation": "@inproceedings{zheng2022MMChat,\nauthor = {Zheng, Yinhe and Chen, Guanyi and Liu, Xin and Sun, Jian},\ntitle = {MMChat: Multi-Modal Chat Dataset on Social Media},\nbooktitle = {Proceedings of The 13th Language Resources and Evaluation Conference},\nyear = {2022},\npublisher = {European Language Resources Association},\n}\n\n@inproceedings{wang2020chinese,\n title = {A Large-Scale Chinese Short-Text Conversation Dataset},\n author = {Wang, Yida and Ke, Pei and Zheng, Yinhe and Huang, Kaili and Jiang, Yong and Zhu, Xiaoyan and Huang, Minlie},\n booktitle = {NLPCC},\n year = {2020},\n url = {https://arxiv.org/abs/2008.03946}\n}\n", "homepage": "https://github.com/silverriver/MMChat", "license": "MIT", "features": {"dialog": [{"dtype": "string", "id": null, "_type": "Value"}], "weibo_content": {"dtype": "string", "id": null, "_type": "Value"}, "imgs": [{"dtype": "string", "id": null, "_type": "Value"}]}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "mmchat", "config_name": "mmchat_lccc_filtered", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 232681680, "num_examples": 492611, "dataset_name": "mmchat"}}, "download_checksums": {"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_lccc_filtered/dialog_lccc_flt.jsonl.gz": {"num_bytes": 33623526, "checksum": "54ad76f67269f1adf3a974acfb71f79299283b1bdefbdb5e2928b8d52b53a64d"}, "https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_lccc_filtered/weibo_img_expanded_url_lccc_flt.jsonl.gz": {"num_bytes": 38226987, "checksum": "6ffd6c8420ef37e6b5a2e88f054f0d5ae849617dea501c3342a512e63ba12a59"}, "https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_lccc_filtered/weibo_lccc_flt.jsonl.gz": {"num_bytes": 34990489, "checksum": "d4900fd5f711fdcc752a60e84edcb6e16fcb9f2100f8b900ccf88af9a780816a"}}, "download_size": 106841002, "post_processing_size": null, "dataset_size": 232681680, "size_in_bytes": 339522682}}
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mmchat.py
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
|
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MMChat is a large-scale dialogue dataset that contains image-grounded dialogues in Chinese.
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Each dialogue in MMChat is associated with one or more images (maximum 9 images per dialogue).
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We design various strategies to ensure the quality of the dialogues in MMChat.
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"""
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import json
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import datasets
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_CITATION = """\
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@inproceedings{zheng2022MMChat,
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author = {Zheng, Yinhe and Chen, Guanyi and Liu, Xin and Sun, Jian},
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title = {MMChat: Multi-Modal Chat Dataset on Social Media},
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booktitle = {Proceedings of The 13th Language Resources and Evaluation Conference},
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year = {2022},
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publisher = {European Language Resources Association},
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-
}
|
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-
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@inproceedings{wang2020chinese,
|
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title = {A Large-Scale Chinese Short-Text Conversation Dataset},
|
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author = {Wang, Yida and Ke, Pei and Zheng, Yinhe and Huang, Kaili and Jiang, Yong and Zhu, Xiaoyan and Huang, Minlie},
|
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booktitle = {NLPCC},
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year = {2020},
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url = {https://arxiv.org/abs/2008.03946}
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}
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"""
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_DESCRIPTION = """\
|
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MMChat is a large-scale dialogue dataset that contains image-grounded dialogues in Chinese.
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Each dialogue in MMChat is associated with one or more images (maximum 9 images per dialogue).
|
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We design various strategies to ensure the quality of the dialogues in MMChat.
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"""
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-
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_HOMEPAGE = "https://github.com/silverriver/MMChat"
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_LICENSE = "MIT"
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-
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_URLS = {
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"mmchat": {
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"train": [
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat/dialog_train.jsonl.gz",
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat/img_url_train.jsonl.gz",
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat/weibo_train.jsonl.gz",
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],
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"dev": [
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat/dialog_dev.jsonl.gz",
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat/img_url_dev.jsonl.gz",
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat/weibo_dev.jsonl.gz",
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],
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"test": [
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat/dialog_test.jsonl.gz",
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat/img_url_test.jsonl.gz",
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat/weibo_test.jsonl.gz",
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],
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},
|
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"mmchat_hf": [
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_hf/dialog.jsonl.gz",
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_hf/weibo_img_expanded_url.jsonl.gz",
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_hf/weibo.jsonl.gz",
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_hf/human_annotation.jsonl.gz",
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],
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"mmchat_raw": [
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_raw/dialog_raw.jsonl.gz",
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_raw/weibo_img_expanded_url_raw.jsonl.gz",
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_raw/weibo_raw.jsonl.gz",
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],
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"mmchat_lccc_filtered": [
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_lccc_filtered/dialog_lccc_flt.jsonl.gz",
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_lccc_filtered/weibo_img_expanded_url_lccc_flt.jsonl.gz",
|
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"https://huggingface.co/datasets/silver/mmchat/resolve/main/mmchat_lccc_filtered/weibo_lccc_flt.jsonl.gz",
|
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],
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}
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-
|
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class MMChat(datasets.GeneratorBasedBuilder):
|
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"""Multi-Modal Chat Dataset."""
|
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-
|
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VERSION = datasets.Version("1.0.0")
|
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BUILDER_CONFIGS = [
|
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datasets.BuilderConfig(name="mmchat", version=VERSION, description="The MMChat dataset"),
|
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datasets.BuilderConfig(name="mmchat_hf", version=VERSION, description="Human filtered version of MMChat"),
|
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-
datasets.BuilderConfig(name="mmchat_raw", version=VERSION, description="Raw dialogues in MMChat"),
|
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datasets.BuilderConfig(name="mmchat_lccc_filtered", version=VERSION, description="LCCC filtered MMChat"),
|
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-
]
|
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-
|
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DEFAULT_CONFIG_NAME = "mmchat"
|
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-
|
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def _info(self):
|
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if self.config.name in ["mmchat", "mmchat_raw", "mmchat_lccc_filtered"]:
|
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features = datasets.Features(
|
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{
|
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-
"dialog": [datasets.Value("string")],
|
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-
"weibo_content": datasets.Value("string"),
|
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-
"imgs": [datasets.Value("string")],
|
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}
|
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-
)
|
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else:
|
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features = datasets.Features(
|
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{
|
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-
"dialog": [datasets.Value("string")],
|
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"weibo_content": datasets.Value("string"),
|
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"imgs": [datasets.Value("string")],
|
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"labels": {
|
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"image_qualified": datasets.Value("bool"),
|
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"dialog_qualified": datasets.Value("bool"),
|
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"dialog_image_related": datasets.Value("bool"),
|
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},
|
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-
}
|
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)
|
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return datasets.DatasetInfo(
|
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-
# This is the description that will appear on the datasets page.
|
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-
description=_DESCRIPTION,
|
128 |
-
# This defines the different columns of the dataset and their types
|
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-
features=features, # Here we define them above because they are different between the two configurations
|
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# If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
|
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-
# specify them. They'll be used if as_supervised=True in builder.as_dataset.
|
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-
# supervised_keys=("sentence", "label"),
|
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# Homepage of the dataset for documentation
|
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homepage=_HOMEPAGE,
|
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# License for the dataset if available
|
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license=_LICENSE,
|
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# Citation for the dataset
|
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-
citation=_CITATION,
|
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)
|
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-
|
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def _split_generators(self, dl_manager):
|
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urls = _URLS[self.config.name]
|
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data_dir = dl_manager.download_and_extract(urls)
|
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-
if self.config.name == "mmchat":
|
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-
return [
|
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-
datasets.SplitGenerator(
|
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-
name=datasets.Split.TRAIN,
|
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-
gen_kwargs={
|
149 |
-
"dialog_file": data_dir["train"][0],
|
150 |
-
"weibo_file": data_dir["train"][2],
|
151 |
-
"img_file": data_dir["train"][1],
|
152 |
-
"label_file": None,
|
153 |
-
},
|
154 |
-
),
|
155 |
-
datasets.SplitGenerator(
|
156 |
-
name=datasets.Split.TEST,
|
157 |
-
gen_kwargs={
|
158 |
-
"dialog_file": data_dir["test"][0],
|
159 |
-
"weibo_file": data_dir["test"][2],
|
160 |
-
"img_file": data_dir["test"][1],
|
161 |
-
"label_file": None,
|
162 |
-
},
|
163 |
-
),
|
164 |
-
datasets.SplitGenerator(
|
165 |
-
name=datasets.Split.VALIDATION,
|
166 |
-
gen_kwargs={
|
167 |
-
"dialog_file": data_dir["dev"][0],
|
168 |
-
"weibo_file": data_dir["dev"][2],
|
169 |
-
"img_file": data_dir["dev"][1],
|
170 |
-
"label_file": None,
|
171 |
-
},
|
172 |
-
),
|
173 |
-
]
|
174 |
-
else:
|
175 |
-
return [
|
176 |
-
datasets.SplitGenerator(
|
177 |
-
name=datasets.Split.TRAIN,
|
178 |
-
gen_kwargs={
|
179 |
-
"dialog_file": data_dir[0],
|
180 |
-
"weibo_file": data_dir[2],
|
181 |
-
"img_file": data_dir[1],
|
182 |
-
"label_file": data_dir[3] if len(data_dir) == 4 else None,
|
183 |
-
},
|
184 |
-
),
|
185 |
-
]
|
186 |
-
|
187 |
-
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
|
188 |
-
def _generate_examples(self, dialog_file, weibo_file, img_file, label_file):
|
189 |
-
id = 0
|
190 |
-
if label_file is not None:
|
191 |
-
label_f = open(label_file, encoding="utf-8")
|
192 |
-
|
193 |
-
with open(dialog_file, encoding="utf-8") as dialog_f, open(weibo_file, encoding="utf-8") as weibo_f, open(
|
194 |
-
img_file, encoding="utf-8"
|
195 |
-
) as img_f:
|
196 |
-
while True:
|
197 |
-
try:
|
198 |
-
dialog_line = dialog_f.readline().strip()
|
199 |
-
if len(dialog_line) == 0:
|
200 |
-
break
|
201 |
-
dialog = json.loads(dialog_line) # dialog_f.readline())
|
202 |
-
weibo = json.loads(weibo_f.readline())
|
203 |
-
if self.config.name == "mmchat":
|
204 |
-
imgs = img_f.readline().strip().split(";")
|
205 |
-
else:
|
206 |
-
imgs = json.loads(img_f.readline())["weibo_img"].split(";")
|
207 |
-
|
208 |
-
if self.config.name == "mmchat_hf":
|
209 |
-
label = json.loads(label_f.readline())
|
210 |
-
# Yields examples as (key, example) tuples
|
211 |
-
yield id, {
|
212 |
-
"dialog": dialog,
|
213 |
-
"weibo_content": weibo,
|
214 |
-
"imgs": imgs,
|
215 |
-
"labels": {
|
216 |
-
"image_qualified": True if label["image_quality"] == "1" else False,
|
217 |
-
"dialog_qualified": True if label["dialog_quality"] == "1" else False,
|
218 |
-
"dialog_image_related": True if label["dialog_image_relativeness"] == "1" else False,
|
219 |
-
},
|
220 |
-
}
|
221 |
-
else:
|
222 |
-
yield id, {
|
223 |
-
"dialog": dialog,
|
224 |
-
"weibo_content": weibo,
|
225 |
-
"imgs": imgs,
|
226 |
-
}
|
227 |
-
id += 1
|
228 |
-
except EOFError:
|
229 |
-
break
|
230 |
-
if label_file is not None:
|
231 |
-
label_f.close()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
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|
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|
|
|
|
|
|
|
mmchat/img_url_test.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:9db4713683a665764085e7480165a7f7c038b2c6239d1c744976298363a5579e
|
3 |
-
size 188377
|
|
|
|
|
|
|
|
mmchat/img_url_train.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:9337c9e96497f0f8d6c01ee30afd7c1feaafd2f669661fe48052f41e3baf7aeb
|
3 |
-
size 5301433
|
|
|
|
|
|
|
|
mmchat/mmchat-test.parquet
ADDED
Binary file (563 kB). View file
|
|
mmchat/{dialog_test.jsonl.gz → mmchat-train.parquet}
RENAMED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
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|
3 |
+
size 15883592
|
mmchat/mmchat-validation.parquet
ADDED
Binary file (140 kB). View file
|
|
mmchat/weibo_dev.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:7f6cef2b570a3aa187d823ab5330806e79f9dd66e4ade4cae78ef7815764d2ee
|
3 |
-
size 101
|
|
|
|
|
|
|
|
mmchat/weibo_test.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:3eaabda17b2e4df3985f6f302f2581ed818a03ae04cc7112f7feb1fcddc4c47b
|
3 |
-
size 189
|
|
|
|
|
|
|
|
mmchat/weibo_train.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:cbcc11ccea2d9dd75047c7fe80ecc3eceaddf555eb2136c5cae78725cb44ed54
|
3 |
-
size 3441
|
|
|
|
|
|
|
|
mmchat_hf/dialog.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:15fcf7756ec5ca39398a4ab9d68d14c403b1f4273781130f90dacb55a862c58a
|
3 |
-
size 6826130
|
|
|
|
|
|
|
|
mmchat_hf/human_annotation.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
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oid sha256:6d34e113027e86f44af220c2c9ce09f909aaff045cd94fd5886b79a972b6e0b4
|
3 |
-
size 358333
|
|
|
|
|
|
|
|
mmchat/dialog_train.jsonl.gz → mmchat_hf/mmchat-train.parquet
RENAMED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
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|
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size 29850386
|
mmchat_hf/weibo.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
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version https://git-lfs.github.com/spec/v1
|
2 |
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|
3 |
-
size 7084046
|
|
|
|
|
|
|
|
mmchat_hf/weibo_img_expanded_url.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:58fccfe34603c92dcb435dde7f7f77f7468dba2df369a412a927d65041f18724
|
3 |
-
size 7781846
|
|
|
|
|
|
|
|
mmchat_lccc_filtered/dialog_lccc_flt.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:54ad76f67269f1adf3a974acfb71f79299283b1bdefbdb5e2928b8d52b53a64d
|
3 |
-
size 33623526
|
|
|
|
|
|
|
|
mmchat/img_url_dev.jsonl.gz → mmchat_lccc_filtered/mmchat-train.parquet
RENAMED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
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size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
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|
3 |
+
size 146847666
|
mmchat_lccc_filtered/weibo_img_expanded_url_lccc_flt.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
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|
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size 38226987
|
|
|
|
|
|
|
|
mmchat_lccc_filtered/weibo_lccc_flt.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
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|
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version https://git-lfs.github.com/spec/v1
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|
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-
size 34990489
|
|
|
|
|
|
|
|
mmchat_raw/dialog_raw.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
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oid sha256:8d36cd302c42eee9a9d39032ff0e1d05975bd5aa2030eecd595e2e2964f6cadf
|
3 |
-
size 389104370
|
|
|
|
|
|
|
|
mmchat_raw/mmchat-train-00000-of-00005.parquet
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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+
oid sha256:ceb51916a61c9034556c4224797191df8d7efcc735154fc3b6132c354fba1981
|
3 |
+
size 339021756
|
mmchat_raw/mmchat-train-00001-of-00005.parquet
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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|
3 |
+
size 339022548
|
mmchat_raw/mmchat-train-00002-of-00005.parquet
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
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|
3 |
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size 339359677
|
mmchat_raw/mmchat-train-00003-of-00005.parquet
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
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oid sha256:1f2a71715cfa8d391d9715119037e1040ef733be522c47e608aa82baf2f4e6bd
|
3 |
+
size 339059862
|
mmchat/dialog_dev.jsonl.gz → mmchat_raw/mmchat-train-00004-of-00005.parquet
RENAMED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
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version https://git-lfs.github.com/spec/v1
|
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|
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size 7634656
|
mmchat_raw/weibo_img_expanded_url_raw.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
version https://git-lfs.github.com/spec/v1
|
2 |
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oid sha256:d0deae3fe9b2bced80ba424fa9110a4e52b583f5823723832ac628e943e0a228
|
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size 268962111
|
|
|
|
|
|
|
|
mmchat_raw/weibo_raw.jsonl.gz
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
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version https://git-lfs.github.com/spec/v1
|
2 |
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oid sha256:d2616195f89040a0cb81d16261293f9ff002d2eb7981eebde2f631069f202521
|
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size 329066732
|
|
|
|
|
|
|
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