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Release harvested InternVideo models on Hugging Face

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评估

难度
4/5
预计耗时
3-5 天
新手友好度
32/100
Issue 类型
功能
描述清晰度
需要澄清
活跃度
停滞
技术栈
huggingface, python, pytorch

调研方向

从链接的 Hugging Face 模型上传指南开始,并识别 issue 中引用的已收集基础模型检查点。完成的标准是:这些检查点托管在 Hugging Face 上,带有便于发现的元数据,并链接到论文页面;issue 不提供任何仓库文件或可运行的测试。

由索引模型根据 Issue 内容生成。

描述

Hi @Revliter 🤗

I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work through Hugging Face's daily papers as yours got featured: https://huggingface.co/papers/2310.19554.
The paper page lets people discuss about your paper and lets them find artifacts about it (your models for instance), you can also claim the paper as yours which will show up on your public profile at HF, add Github and project page URLs.

I see that the InternVideo project is already very active on Hugging Face with InternVideo2 and InternVideo2.5. Would you like to also host the foundation model checkpoints you've pre-trained using the "harvesting" framework on https://huggingface.co/models?

Hosting on Hugging Face will give these specific models more visibility and enable better discoverability within the community. We can add metadata tags to the model cards so that people find them easier when filtering for video-language tasks, and link them directly to the paper page.

If you're down, I'm leaving a guide here. If they are custom models, you can use the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub functionality, or simply use hf_hub_download for easy checkpoint access.

After uploaded, we can link the models to the paper page (read here) so people can discover your work.

Let me know if you're interested or need any guidance!

Kind regards,

Niels

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Python
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PR 合并指标
30 天内没有已合并 PR

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  2. 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
  3. Fork 仓库,在一个分支上完成修改。
  4. 提交 Pull Request,并在描述里引用这个 Issue 编号。

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