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As a potential user of this project, I am interested in training 3D Gaussian splatting models on my own dataset. However, I am using a moderately capable graphics card, and I want to avoid long traini…
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LightGBM:
Efficiency: LightGBM is designed to be highly efficient and can handle large datasets with faster training times.
Accuracy: It often provides better accuracy compared to other gradient b…
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🔍 Problem Description:
The flight delay prediction model aims to predict if a flight will be delayed based on factors like airline, origin, destination, departure time, and day of the week. This help…
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LINK TO GRAYSCALE MNIST: https://github.com/Seqaeon/MNIST_streamlit
Our weightless neural networks framework running on MNIST and MNIST-grayscale already achieves great results in terms of traini…
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[meta engineering blog post](https://engineering.fb.com/2024/06/12/data-infrastructure/training-large-language-models-at-scale-meta/)
- Meta requires massive computational power to train large lang…
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### Motivation
Is it possible to apply Mixed Preference Optimization for 76B internVL. Similar to 8B but for 76B?
### Related resources
_No response_
### Additional context
_No response_
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Hi,
I am trying to fine-tune a Llama model with a large context size, and I found that to efficiently shard activations across multiple GPUs, I need to use Torchtitan. Here are some questions relat…
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(AI_Scientist) root@intern-studio-50102651:~/AI-Scientist# python launch_scientist.py --model "gpt-4o-2024-05-13" --experiment nanoGPT --num-ideas 1
Using GPUs: [0]
Using OpenAI API with model gpt-4…
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I'm interested in having support for [cost-efficient gradient boosting](https://dl.acm.org/doi/pdf/10.5555/3294771.3294919) in XGBoost. Glossing over non-essential details, CEBG is the application of …
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### Feature request
Pytorch XLA/PJRT TPU support for bitsandbytes
### Motivation
Would allow for faster and more memory efficient training of models on TPUs.
### Your contribution
Happy to prov…