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Add training for the llama2.c example (#296)

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* Rework the commands and run inference by default.

* Add the training module and load the training dataset.

* Random dataset iterator.

* Proper valid-loss computation.

* Compute the evaluation loss.

* Add more substance to the training loop.
This commit is contained in:
Laurent Mazare
2023-08-01 17:23:07 +01:00
committed by GitHub
parent babee9f011
commit a27239f3d9
6 changed files with 227 additions and 9 deletions
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3
candle-examples/Cargo.toml
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@ -26,8 +26,9 @@ half = { workspace = true, optional = true }
[dev-dependencies]
anyhow = { workspace = true }
byteorder = { workspace = true }
hf-hub = { workspace = true}
clap = { workspace = true }
hf-hub = { workspace = true }
memmap2 = { workspace = true }
rand = { workspace = true }
tokenizers = { workspace = true, features = ["onig"] }
tracing = { workspace = true }