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Update docs and bump to 0.2.0-dev (#16)
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RELEASE.md

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@@ -15,7 +15,7 @@ is a bit more involved than it would be otherwise.
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3. This will kick off the "Build precompiled NIFs" GitHub Action. Wait for this to complete. It
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usually takes around 40-60 minutes.
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4. While the NIFs are compiling, ensure you have the latest version of `main` and don't have any
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intermediate builds by running `rm -rf native/explorer/target`.
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5. Once the NIFs are built, use `mix rustler_precompiled.download Explorer.PolarsBackend.Native --all --print` to download generate the checksum file.
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intermediate builds by running `rm -rf native/ex_tokenizers/target`.
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5. Once the NIFs are built, use `mix rustler_precompiled.download Tokenizers.Native --all --print` to download generate the checksum file.
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6. Run `mix hex.publish`.
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7. Bump the version in the `mix.exs` and add the `-dev` flag to it.

flake.lock

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flake.nix

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cc
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clang
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clippy
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elixir
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elixir_1_14
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erlang
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gdb
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gcc
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darwin.apple_sdk.frameworks.Carbon
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darwin.apple_sdk.frameworks.AppKit
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];
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shellHook = ''
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mkdir -p .nix-mix
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mkdir -p .nix-hex
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export MIX_HOME=$PWD/.nix-mix
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export HEX_HOME=$PWD/.nix-hex
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export PATH=$MIX_HOME/bin:$PATH
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export PATH=$HEX_HOME/bin:$PATH
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export PATH=$MIX_HOME/escripts:$PATH
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export ERL_AFLAGS="-kernel shell_history enabled"
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'';
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};
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});
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shellHook = ''
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mkdir -p .nix-mix
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mkdir -p .nix-hex
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export MIX_HOME=$PWD/.nix-mix
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export HEX_HOME=$PWD/.nix-hex
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export PATH=$MIX_HOME/bin:$PATH
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export PATH=$HEX_HOME/bin:$PATH
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export PATH=$MIX_HOME/escripts:$PATH
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export ERL_AFLAGS="-kernel shell_history enabled"
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'';
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};
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});
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}

mix.exs

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use Mix.Project
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@source_url "https://github.com/elixir-nx/tokenizers"
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@version "0.1.0"
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@version "0.2.0-dev"
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def project do
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[

notebooks/pretrained.livemd

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Typically the reason we're tokenizing text is to use it as an input in a machine learning model. For that, we'll need tensors.
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In order to get a tensor, we need sequences that are all of the same length. We'll get some data from `Scidata` and use `Tokenizers.pad/3` and `Tokenizers.truncate/3` to yield a tensor.
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In order to get a tensor, we need sequences that are all of the same length. We'll get some data from `Scidata` and use `Tokenizers.Encoding.pad/3` and `Tokenizers.Encoding.truncate/3` to yield a tensor.
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```elixir
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%{review: reviews} = Scidata.YelpPolarityReviews.download_test()

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