remove webinstructweb

README.md

@@ -31,7 +31,6 @@ The goal of general-purpose datasets is to transform base models into versatile
 | Dataset | # | Authors | Date | Notes |
 | ------------------------------------------------------------------------------------------------------------- | ----- | ---------------------------- | -------- | --------------------------------------------------------------------------------- |
 | 🆕 [Buzz](https://huggingface.co/datasets/H-D-T/Buzz) | 31.2M | Alignment Lab AI | May 2024 | Huge collection of 435 datasets with data augmentation, deduplication, and other techniques. |
-| 🆕 [WebInstructSub](https://huggingface.co/datasets/TIGER-Lab/WebInstructSub) | 2.39M | Yue et al. | May 2024 | Instructions created by retrieving document from Common Crawl, extracting QA pairs, and refining them. See the [MAmmoTH2 paper](https://arxiv.org/abs/2405.03548) (this is a subset). |
 | [Bagel](https://github.com/jondurbin/bagel) | >2M? | Jon Durbin | Jan 2024 | Collection of datasets decontaminated with cosine similarity. |
 | [Hercules v4.5](https://huggingface.co/datasets/Locutusque/hercules-v4.5) | 1.72M | Sebastian Gabarain | Apr 2024 | Large-scale general-purpose dataset with math, code, RP, etc. See [v4](https://huggingface.co/datasets/Locutusque/hercules-v4.0) for the list of datasets. |
 | [Dolphin-2.9](https://huggingface.co/datasets/cognitivecomputations/Dolphin-2.9) | 1.39M | Cognitive Computations | Apr 2023 | Large-scale general-purpose dataset used by the Dolphin models. |