Comments (5)
NeroBlackstone
commented on June 24, 2024
2
I'm started to rewriting Julia version in this repository
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AnirudhDagar
commented on June 24, 2024
1
Thanks @NeroBlackstone, that sounds like a fun fork of the project! Good luck. :)
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AnirudhDagar
commented on June 24, 2024
1
Hi @NeroBlackstone, atm we don't have the capacity to maintain the project. I'll keep this issue open and for anyone who is interested can check out your fork https://github.com/NeroBlackstone/D2lJulia and contribute more sections there.
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NeroBlackstone
commented on June 24, 2024
I have finished chapter 2 - Preliminaries. d2ljulia
For anyone who want to contribute, please open a pull request at d2ljulia
:)
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NeroBlackstone
commented on June 24, 2024
Transfer request:
If D2l organization wants to adopt this fork, I'm willing to transfer the repository to D2l organization.
I'll continue to maintain this fork, and hope to get contributions from the Julia machine learning community.
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Related Issues (20)
- Ethics?
- MLX support HOT 1
- Add type hinting to functions HOT 1
- Incorrect Use of torch.no_grad() in fit_epoch Method in d2l/torch.py::Trainer::fit_epoch HOT 2
- Not able to render :begin_tab:toc
- Errors in train_ch3 in tensorflow version softmax-regression-scratch.ipynb HOT 1
- [**emergency**] the comment block is down, please fix it right now HOT 1
- Chinese version of the code is out of date
- The discussion link can not be accessed. HOT 7
- The mlm loss computation in the function _get_batch_loss_bert seems wrong in d2l pytorch code HOT 2
- Can't build the book on MacOS when trying to add MLX implementation
- Some issues with the book
- WikiText-2 is not a zip file HOT 3
- question about ”d2l = sys.modules[__name__]“
- Website of preview version is down. HOT 5
- The content is outdated
- nn.dataparallel has issue for mac (mps device)
- AttributeError: partially initialized module 'charset_normalizer' has no attribute 'md__mypyc' (most likely due to a circular import)
- Addition of dark mode
- d2l.Seq2SeqEncoder(vocab_size=10, embed_size=8, num_hiddens=16, 2 num_layers=2) HOT 2
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