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barthfab
updated
a
dataset
4 days ago
Post
838
🇹🇷 😍 I'm very happy to finally announce my new Turkish LM called "BERT5urk":
stefan-it/bert5urk
It is a 1.42B T5-based model, trained with UL2 pretraining objective on the Turkish part of the awesome HuggingFaceFW/fineweb-2 dataset.
Feel free to check it out!
stefan-it/bert5urk
It is a 1.42B T5-based model, trained with UL2 pretraining objective on the Turkish part of the awesome HuggingFaceFW/fineweb-2 dataset.
Feel free to check it out!
- 1 reply
Post
3113
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]:
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:
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:
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
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]:
sudo apt -y install cuda-toolkit-12-8 nvidia-openI 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/cu128After 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
- 1 reply
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#6 opened 16 days ago
by
StarscreamDeceptions
Post
5069
She arrived 😍
[Expect more models soon...]
[Expect more models soon...]
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- 2 replies
malteos
authored
10
papers
21 days ago
Tokenizer Choice For LLM Training: Negligible or Crucial?
Paper
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2310.08754
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Published
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2
Towards an Open Platform for Legal Information
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2005.13342
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Published
Aspect-based Document Similarity for Research Papers
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2010.06395
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Published
Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings
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2202.06671
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2
Specialized Document Embeddings for Aspect-based Similarity of Research Papers
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2203.14541
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Published
Investigating Gender Bias in Turkish Language Models
Paper
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2404.11726
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Published
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1
Efficient Language Model Training through Cross-Lingual and Progressive Transfer Learning
Paper
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2301.09626
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Published
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2
Progress Report: Towards European LLMs
Paper
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2410.03730
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Published
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2
Data Processing for the OpenGPT-X Model Family
Paper
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2410.08800
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Published
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1
MMTEB: Massive Multilingual Text Embedding Benchmark
Paper
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2502.13595
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Published
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32
PSaiml
authored
a
paper
about 2 months ago
s-conia
authored
4
papers
about 2 months ago
ZEBRA: Zero-Shot Example-Based Retrieval Augmentation for Commonsense Question Answering
Paper
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2410.05077
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Published
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2
Echoes from Alexandria: A Large Resource for Multilingual Book Summarization
Paper
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2306.04334
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Published
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2
Semantic Role Labeling Meets Definition Modeling: Using Natural Language to Describe Predicate-Argument Structures
Paper
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2212.01094
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Published
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2
Do Large Language Models Have an English Accent? Evaluating and Improving the Naturalness of Multilingual LLMs
Paper
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2410.15956
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Published