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Fine-tune Flair Models on NER Dataset with 🤗 AutoTrain SpaceRunner
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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
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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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