Hi @NoakLiu 馃
I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work on Arxiv and was wondering whether you would like to submit it to hf.co/papers to improve its discoverability. If you are one of the authors, you can submit it at https://huggingface.co/papers/submit.
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 saw that you've released the system code for SPI on GitHub (https://github.com/FastLM/SPI_VecDB). Would you also like to host the pre-trained model checkpoints you've developed (specifically the lightweight residual refinement encoders and the uncertainty-aware controller) on https://huggingface.co/models?
Hosting on Hugging Face will give your work more visibility and enable better discoverability within the RAG and vector database communities. We can add metadata tags to the model cards so that people find the models easier and link them directly to the paper page.
If you're down, leaving a guide here. If it's a custom PyTorch model, you can use the PyTorchModelHubMixin class which adds from_pretrained and push_to_hub to the model, allowing people to download and use them right away. Alternatively, you can use hf_hub_download for simple checkpoint management.
After uploaded, we can also link the models to the paper page (read here) so people can discover your work.
Let me know if you're interested/need any guidance :)
Kind regards,
Niels
Hi @NoakLiu 馃
I'm Niels and work as part of the open-source team at Hugging Face. I discovered your work on Arxiv and was wondering whether you would like to submit it to hf.co/papers to improve its discoverability. If you are one of the authors, you can submit it at https://huggingface.co/papers/submit.
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 saw that you've released the system code for SPI on GitHub (https://github.com/FastLM/SPI_VecDB). Would you also like to host the pre-trained model checkpoints you've developed (specifically the lightweight residual refinement encoders and the uncertainty-aware controller) on https://huggingface.co/models?
Hosting on Hugging Face will give your work more visibility and enable better discoverability within the RAG and vector database communities. We can add metadata tags to the model cards so that people find the models easier and link them directly to the paper page.
If you're down, leaving a guide here. If it's a custom PyTorch model, you can use the PyTorchModelHubMixin class which adds
from_pretrainedandpush_to_hubto the model, allowing people to download and use them right away. Alternatively, you can use hf_hub_download for simple checkpoint management.After uploaded, we can also link the models to the paper page (read here) so people can discover your work.
Let me know if you're interested/need any guidance :)
Kind regards,
Niels