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Simplify the setup in CI (#542)
* Simplify the setup in CI * windows --no-binary option * windows uv workflow * add path * some fixes * some fixes * some fixes * cleanup * cleanup * cleanup * cleanup * cleanup * more windows issues * more windows issues * more windows issues * more windows issues * more windows issues * more windows issues * more windows issues * more windows issues * revert
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@@ -50,7 +50,7 @@ If it returns 3.10 or newer, no further action is required.
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> [!NOTE]
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> I recommend installing a Python version that is at least 1-3 versions older than the most recent release to ensure PyTorch compatibility. For example, if the most recent version is Python 3.13, I recommend installing version 3.10, 3.11, or 3.12.
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> I recommend installing a Python version that is at least 2 versions older than the most recent release to ensure PyTorch compatibility. For example, if the most recent version is Python 3.13, I recommend installing version 3.10 or 3.11.
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Otherwise, if Python is not installed or is an older version, you can install it for your operating system as described below.
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@@ -62,7 +62,7 @@ Otherwise, if Python is not installed or is an older version, you can install it
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```bash
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sudo apt update
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sudo apt install python3.11 python3.11-venv python3.11-dev
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sudo apt install python3.10 python3.10-venv python3.10-dev
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```
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<br>
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@@ -143,13 +143,13 @@ uv pip install packaging
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To install all required packages from a `requirements.txt` file (such as the one located at the top level of this GitHub repository) run the following command, assuming the file is in the same directory as your terminal session:
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```bash
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uv pip install -U -r requirements.txt
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uv pip install -r requirements.txt
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```
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Alternatively, install the latest dependencies directly from the repository:
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```bash
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uv pip install -U -r https://raw.githubusercontent.com/rasbt/LLMs-from-scratch/refs/heads/main/requirements.txt
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uv pip install -r https://raw.githubusercontent.com/rasbt/LLMs-from-scratch/refs/heads/main/requirements.txt
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```
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@@ -246,7 +246,7 @@ conda create -n LLMs python=3.10
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<img src="https://sebastianraschka.com/images/LLMs-from-scratch-images/setup/01_optional-python-setup-preferences/new-env.png" alt="new-env" width="600px">
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> Many scientific computing libraries do not immediately support the newest version of Python. Therefore, when installing PyTorch, it's advisable to use a version of Python that is one to three releases older. For instance, if the latest version of Python is 3.13, using Python 3.10, 3.11, or 3.12 is recommended.
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> Many scientific computing libraries do not immediately support the newest version of Python. Therefore, when installing PyTorch, it's advisable to use a version of Python that is one or two releases older. For instance, if the latest version of Python is 3.13, using Python 3.10 or 3.11 is recommended.
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Next, activate your new virtual environment (you have to do it every time you open a new terminal window or tab):
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@@ -70,6 +70,8 @@ uv sync --dev --python 3.11
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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 regular pip:
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> `uv add pip`
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> `uv run python -m pip install -U -r requirements.txt`
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>
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> Since the TensorFo
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