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Stefan Schweter PRO

stefan-it

AI & ML interests

Flair Library 💕, NER & PoS Tagging, LM Pretraining (mostly encoder-only & encoder-decoder), Historical Language Models

Recent Activity

liked a model about 7 hours ago

chandar-lab/NeoBERT

commented on a paper about 7 hours ago

NeoBERT: A Next-Generation BERT

posted an update about 18 hours ago

After running some 3DMark and FurMark benchmarks on Windows to make sure that my new 5090 is not causing melting cables [1] and some nice shots with a thermal camera (I don't think that's too much), running some fine-tuning experiments with my favorite Flair & Transformers libraries are very easy to perform. Important steps: Good idea is to start with a fresh Ubuntu 24.04 installation with latest CUDA 12.8 and the open NVIDIA driver - follow more advices from [2]: ```bash sudo apt -y install cuda-toolkit-12-8 nvidia-open ``` I tried update from an existing Ubuntu installation with an older CUDA and driver version and it resulted in a non-startable system. If you are using PyTorch 2.6 with built CUDA 12.6 it will result in: ```bash NVIDIA Graphics Device with CUDA capability sm_120 is not compatible with the current PyTorch installation. The current PyTorch install supports CUDA capabilities sm_50 sm_60 sm_70 sm_75 sm_80 sm_86 sm_90. ``` But no worries! For PyTorch you need just to use a nightly 2.7 version that was built with CUDA 12.8. This can easily done via: ```bash pip install --pre torch --index-url https://download.pytorch.org/whl/nightly/cu128 ``` After that the latest Flair version can be installed and fine-tuning will work! References: [1]: https://www.reddit.com/r/nvidia/comments/1inpox7/rtx_50_series_12vhpwr_megathread/ [2]: https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu&target_version=24.04&target_type=deb_network

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stefan-it's activity

liked a model about 7 hours ago

chandar-lab/NeoBERT

Updated about 12 hours ago • 17 • 15

commented a paper about 7 hours ago

NeoBERT: A Next-Generation BERT

Paper • 2502.19587 • Published 2 days ago • 8 •

posted an update about 18 hours ago

Post

1077

sudo apt -y install cuda-toolkit-12-8 nvidia-open

I tried update from an existing Ubuntu installation with an older CUDA and driver version and it resulted in a non-startable system.

If you are using PyTorch 2.6 with built CUDA 12.6 it will result in:

NVIDIA Graphics Device with CUDA capability sm_120 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_50 sm_60 sm_70 sm_75 sm_80 sm_86 sm_90.

But no worries! For PyTorch you need just to use a nightly 2.7 version that was built with CUDA 12.8. This can easily done via:

pip install --pre torch --index-url https://download.pytorch.org/whl/nightly/cu128

After that the latest Flair version can be installed and fine-tuning will work!

References:

[1]: https://www.reddit.com/r/nvidia/comments/1inpox7/rtx_50_series_12vhpwr_megathread/
[2]: https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu&target_version=24.04&target_type=deb_network

reacted to jsulz's post with 🚀 about 19 hours ago

Post

3292

Time flies!

Six months after joining Hugging Face the Xet team is kicking off the first migrations from LFS to our storage for a number of repositories on the Hub.

More on the nitty gritty details behind the migration soon, but here are the big takeaways:

🤖 We've successfully completed the first migrations from LFS -> Xet to test the infrastructure and prepare for a wider release

✅ No action on your part needed - you can work with a Xet-backed repo like any other repo on the Hub (for now - major improvements on their way!)

👀 Keep an eye out for the Xet logo to see if a repo you know is on our infra! See the screenshots below to spot the difference 👇

⏩ ⏩ ⏩ Blazing uploads and downloads coming soon. W’re gearing up for a full integration with the Hub's Python library that will make building on the Hub faster than ever - special thanks to @celinah and @Wauplin for their assistance.

🎉 Want Early Access? If you’re curious and want to test it out the bleeding edge that will power the development experience on the Hub, we’d love to partner with you. Let me know!

This is the culmination of a lot of effort from the entire team. Big round of applause to @sirahd @brianronan @jgodlewski @hoytak @seanses @assafvayner @znation @saba9 @rajatarya @port8080 @yuchenglow