blog
awesome-notebooks
| blog | awesome-notebooks | |
|---|---|---|
| 5 | 1 | |
| 2,011 | 2,294 | |
| 5.0% | 1.2% | |
| 9.8 | 9.9 | |
| 4 days ago | 3 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
blog
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Refact LLM: New 1.6B code model reaches 32% HumanEval and is SOTA for the size
[4] https://github.com/huggingface/blog/blob/main/starcoder.md
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A comprehensive guide to running Llama 2 locally
If you just want to do inference/mess around with the model and have a 16GB GPU, then this[0] is enough to paste into a notebook. You need to have access to the HF models though.
0. https://github.com/huggingface/blog/blob/main/llama2.md#usin...
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Letโs train your first Offline Decision Transformer model from scratch ๐ค
The hands-on ๐https://github.com/huggingface/blog/blob/main/notebooks/101_train-decision-transformers.ipynb
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How to switch to half precision fp16?
I'm also running the optimized script but it doesn't run with 512x512 on my RTX3050 Ti mobile. On this website, they recommend to switch to fp16 for GPUs with less than 10gb of vram.
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Are people hiding their deep learning code?
Here's a notebook illustrating how to train a language model from scratch: https://github.com/huggingface/blog/blob/master/notebooks/01_how_to_train.ipynb
awesome-notebooks
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