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| author | Laurent Mazare <laurent.mazare@gmail.com> | 2023-10-25 21:51:45 +0100 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2023-10-25 21:51:45 +0100 |
| commit | e7b886d56f05b30b7814e0aaf0aea505fcfe30d2 (patch) | |
| tree | a66c1e46fb9be13be36f13242b39a8185032745d /README.md | |
| parent | 6a446d9d73da64daea4dc75e9b57dba78d4180fb (diff) | |
| download | candle-e7b886d56f05b30b7814e0aaf0aea505fcfe30d2.tar.gz candle-e7b886d56f05b30b7814e0aaf0aea505fcfe30d2.tar.bz2 candle-e7b886d56f05b30b7814e0aaf0aea505fcfe30d2.zip | |
Add a link to the optimisers crate. (#1180)
Diffstat (limited to 'README.md')
| -rw-r--r-- | README.md | 2 |
1 files changed, 2 insertions, 0 deletions
@@ -135,6 +135,8 @@ And then head over to ## Useful External Resources - [`candle-tutorial`](https://github.com/ToluClassics/candle-tutorial): a very detailed tutorial showing how to convert a PyTorch model to Candle. +- [`optimisers`](https://github.com/KGrewal1/optimisers): a collection of optimisers + including SGD with momentum, AdaGrad, AdaDelta, AdaMax, NAdam, RAdam, and RMSprop. - [`candle-lora`](https://github.com/EricLBuehler/candle-lora): a LoRA implementation that conforms to the official `peft` implementation. |