Update README.md

README.md

@@ -11,17 +11,17 @@ multilinguality:
 size_categories:
 - 1M<n<10M
 source_datasets:
-- https://huggingface.co/datasets
+- https://github.com/shibing624/text2vec
 task_categories:
 - text-classification
 task_ids:
 - natural-language-inference
 - semantic-similarity-scoring
 - text-scoring
-paperswithcode_id: snli
-pretty_name: Stanford Natural Language Inference
+paperswithcode_id: nli
+pretty_name: Chinese Natural Language Inference
 ---
-# Dataset Card for SNLI_zh
+# Dataset Card for nli-zh-all
 
 ## Dataset Description
 - **Repository:** [Chinese NLI dataset](https://github.com/shibing624/text2vec)
@@ -35,9 +35,6 @@ pretty_name: Stanford Natural Language Inference
 整合了文本推理，相似，摘要，问答，指令微调等任务的820万高质量数据，并转化为匹配格式数据集。
 
 
-
-
-
 ### Supported Tasks and Leaderboards
 
 Supported Tasks: 支持中文文本匹配任务，文本相似度计算等相关任务。
@@ -70,7 +67,6 @@ The data fields are the same among all splits.
 
 after remove None and len(text) < 1 data:
 ```shell
-
 $ wc -l nli-zh-all/*
    48818 nli-zh-all/alpaca_gpt4-train.jsonl
     5000 nli-zh-all/amazon_reviews-train.jsonl
@@ -91,13 +87,14 @@ $ wc -l nli-zh-all/*
    93404 nli-zh-all/xlsum-train.jsonl
  1006218 nli-zh-all/zhihu_kol-train.jsonl
  8234680 total
-
 ```
 
 ### Data Length
 
 ![len](https://huggingface.co/datasets/shibing624/nli-zh-all/resolve/main/nli-zh-all-len.png)
 
+count text length script: https://github.com/shibing624/text2vec/blob/master/examples/data/count_text_length.py
+
 ## Dataset Creation
 ### Curation Rationale
 受[m3e-base](https://huggingface.co/moka-ai/m3e-base#M3E%E6%95%B0%E6%8D%AE%E9%9B%86)启发，合并了中文高质量NLI(natural langauge inference)数据集，
@@ -132,7 +129,8 @@ $ wc -l nli-zh-all/*
 #### Who are the source language producers?
 数据集的版权归原作者所有，使用各数据集时请尊重原数据集的版权。
 
-- SNLI:
+SNLI:
+
 @inproceedings{snli:emnlp2015,
     Author = {Bowman, Samuel R. and Angeli, Gabor and Potts, Christopher, and Manning, Christopher D.},
     Booktitle = {Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP)},