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author | Nicolas Patry <patry.nicolas@protonmail.com> | 2023-08-14 10:52:12 +0200 |
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committer | Nicolas Patry <patry.nicolas@protonmail.com> | 2023-08-28 15:14:17 +0200 |
commit | 76023236677fbab10fd1c99eab95d268416fb941 (patch) | |
tree | 7d4ba218664bfb148b4d9ff8dcdd0155630b538b /candle-book | |
parent | 9137c631755ad945ebdb939d24e6c5e191b8b5c2 (diff) | |
download | candle-76023236677fbab10fd1c99eab95d268416fb941.tar.gz candle-76023236677fbab10fd1c99eab95d268416fb941.tar.bz2 candle-76023236677fbab10fd1c99eab95d268416fb941.zip |
[Book] Add small error management + start training (with generic dataset
inclusion).
Diffstat (limited to 'candle-book')
-rw-r--r-- | candle-book/src/SUMMARY.md | 10 | ||||
-rw-r--r-- | candle-book/src/training/README.md | 16 |
2 files changed, 21 insertions, 5 deletions
diff --git a/candle-book/src/SUMMARY.md b/candle-book/src/SUMMARY.md index 3432f66f..6eadb0c1 100644 --- a/candle-book/src/SUMMARY.md +++ b/candle-book/src/SUMMARY.md @@ -12,7 +12,11 @@ - [Running a model](inference/README.md) - [Using the hub](inference/hub.md) -- [Error management]() +- [Error management](error_manage.md) +- [Training](training/README.md) + - [MNIST]() + - [Fine-tuning]() + - [Serialization]() - [Advanced Cuda usage]() - [Writing a custom kernel]() - [Porting a custom kernel]() @@ -21,7 +25,3 @@ - [Creating a WASM app]() - [Creating a REST api webserver]() - [Creating a desktop Tauri app]() -- [Training]() - - [MNIST]() - - [Fine-tuning]() - - [Serialization]() diff --git a/candle-book/src/training/README.md b/candle-book/src/training/README.md index 8977de34..f4f9eb85 100644 --- a/candle-book/src/training/README.md +++ b/candle-book/src/training/README.md @@ -1 +1,17 @@ # Training + + +Training starts with data. We're going to use the huggingface hub and +start with the Hello world dataset of machine learning, MNIST. + +Let's start with downloading `MNIST` from [huggingface](https://huggingface.co/datasets/mnist). + + +```rust +use candle_datasets::from_hub; + + +let dataset = from_hub("mnist")?; +``` + +This uses the standardized `parquet` files from the `refs/convert/parquet` branch on every dataset. |