Hi @rappysaha 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 in your GitHub README that you're planning to release the code and several PoT-quantized model checkpoints (such as the MobileNetV2 model trained from scratch on CIFAR-10). Would you like to host these pre-trained weights on https://huggingface.co/models when they are ready?
Hosting on Hugging Face will give you more visibility and enable better discoverability. We can add tags in the model cards so that people find the models easier, link them directly to the paper page, and track download statistics. Since your pipeline utilizes TensorFlow Lite for deployment, you can host the .tflite checkpoints directly on the Hub, making them easily accessible for edge device developers.
If you're down, leaving a guide here. You can also use the huggingface_hub library to programmatically upload and download checkpoints using hf_hub_download.
After uploaded, we can also link the models to the paper page (read here) so people can discover your work more effectively.
Let me know if you're interested or if you need any guidance :)
Kind regards,
Niels
ML Engineer @ HF 馃
Hi @rappysaha 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 in your GitHub README that you're planning to release the code and several PoT-quantized model checkpoints (such as the MobileNetV2 model trained from scratch on CIFAR-10). Would you like to host these pre-trained weights on https://huggingface.co/models when they are ready?
Hosting on Hugging Face will give you more visibility and enable better discoverability. We can add tags in the model cards so that people find the models easier, link them directly to the paper page, and track download statistics. Since your pipeline utilizes TensorFlow Lite for deployment, you can host the
.tflitecheckpoints directly on the Hub, making them easily accessible for edge device developers.If you're down, leaving a guide here. You can also use the
huggingface_hublibrary to programmatically upload and download checkpoints using hf_hub_download.After uploaded, we can also link the models to the paper page (read here) so people can discover your work more effectively.
Let me know if you're interested or if you need any guidance :)
Kind regards,
Niels
ML Engineer @ HF 馃