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Uv workflow improvements (#531)
* Uv workflow improvements * Uv workflow improvements * linter improvements * pytproject.toml fixes * pytproject.toml fixes * pytproject.toml fixes * pytproject.toml fixes * pytproject.toml fixes * pytproject.toml fixes * windows fixes * windows fixes * windows fixes * windows fixes * windows fixes * windows fixes * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix * win32 fix
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@@ -22,7 +22,7 @@ This section guides you through the Python setup and package installation proced
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>
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> If you prefer the native `uv` commands, refer to the [./native-uv.md tutorial](./native-uv.md). I also recommend checking the official [`uv` documentation](https://docs.astral.sh/uv/).
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>
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> While `uv add` offers speed advantages, I find `uv pip` slightly more user-friendly, making it a good starting point for beginners. However, if you're new to Python package management, the native `uv` interface is also a great way to learn.
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> While `uv add` offers additional speed advantages, I think that `uv pip` is slightly more user-friendly, making it a good starting point for beginners. However, if you're new to Python package management, the native `uv` interface is also a great opportunity to learn it from the start. It's also how I use `uv` now, but I realize it the barrier to entry is a bit higher if you are coming from `pip` and `conda`.
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@@ -146,6 +146,10 @@ uv pip install -U -r https://raw.githubusercontent.com/rasbt/LLMs-from-scratch/r
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<img src="https://sebastianraschka.com/images/LLMs-from-scratch-images/setup/uv-setup/uv-install.png" width="700" height="auto" alt="Uv install">
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> [!NOTE]
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> If you have problems with the following commands above due to certain dependencies (for example, if you are using Windows), you can always fall back to using regular pip:
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> `pip install -r requirements.txt`
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<br>
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**Finalizing the setup**
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