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Implementing a storage quota and effectively managing capacity could be crucial for enhancing Codabench's scalability and ensuring long-term service availability in production.
# Features
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## 🔨Work Item
**IMPORTANT:**
* This template is only for dev team to track project progress. For feature request or bug report, please use the corresponding issue templates.
* DO NOT create a new…
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### Prerequisite
- [X] I have searched [Issues](https://github.com/open-mmlab/mmdetection/issues) and [Discussions](https://github.com/open-mmlab/mmdetection/discussions) but cannot get the expected …
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Hello,
Thank you for putting out this amazing set of models, datasets and evals!
Is it possible to release the code and details for the VideoChat2-text baseline from your paper? I am studying some…
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Thanks for the great work!
In paper FLMR, I saw there are two external datasets _Google Search Corpus_ and _Wikipedia Corpus_, used for OK-VQA task. I saw the Google Search Corpus [here](https://driv…
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## Description
Compile a list of various corpora from different domains, for evaluation of implemented algorithms against other popular topic modelling techniques. Ideally, selected corpus should h…
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I've been doing some more work with this repo, and I think it'd be productive to do some benchmarking beyond the given example. For example I've started working with the wiki8 text corpus (first 10^8 …
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Hi! Awesome work and datasets collection! Is there a way (or plan to release such a script) to launch a model's benchmark evaluation on the full set of data and obtain a comprehensive report on all th…
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As noted in #637, job execution times can be significantly lengthened by certain implementation details due to the IO characteristics of object-store-backed DMOD _Datasets_. Many practical job tests …
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in keeping with `torchvision` structure of package