add bash script to install packages

README.md

@@ -84,7 +84,16 @@ All notebooks are **beginner friendly**! Add your dataset, click "Run All", and
 
 ![](https://i.ibb.co/sJ7RhGG/image-41.png)
 
-## 💾 Installation Instructions
+## 💾 Simple Installation Instructions
+
+```bash
+./install.sh
+```
+
+## 💾 Manual Installation Instructions
+<details>
+<summary>Details</summary>
+
 ### Conda Installation
 Select either `pytorch-cuda=11.8` for CUDA 11.8 or `pytorch-cuda=12.1` for CUDA 12.1. If you have `mamba`, use `mamba` instead of `conda` for faster solving. See this [Github issue](https://github.com/unslothai/unsloth/issues/73) for help on debugging Conda installs.
 ```bash
@@ -93,7 +102,7 @@ conda activate unsloth_env
 
 conda install pytorch-cuda=<12.1/11.8> pytorch cudatoolkit xformers -c pytorch -c nvidia -c xformers
 
-pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
+pip install "unsloth[colab-221] @ git+https://github.com/unslothai/unsloth.git"
 
 pip install --no-deps trl peft accelerate bitsandbytes
 ```
@@ -138,27 +147,28 @@ pip install "unsloth[cu121-torch220] @ git+https://github.com/unslothai/unsloth.
 pip install "unsloth[cu118-ampere-torch220] @ git+https://github.com/unslothai/unsloth.git"
 pip install "unsloth[cu121-ampere-torch220] @ git+https://github.com/unslothai/unsloth.git"
 ```
-5. If you get errors, try the below first, then go back to step 1:
-```bash
-pip install --upgrade pip
-```
-6. For Pytorch 2.2.1:
+5. For Pytorch 2.2.1:
 ```bash
 # RTX 3090, 4090 Ampere GPUs:
-pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
+pip install "unsloth[colab-221] @ git+https://github.com/unslothai/unsloth.git"
 pip install --no-deps packaging ninja einops flash-attn xformers trl peft accelerate bitsandbytes
 
 # Pre Ampere RTX 2080, T4, GTX 1080 GPUs:
-pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
+pip install "unsloth[colab-221] @ git+https://github.com/unslothai/unsloth.git"
 pip install --no-deps xformers trl peft accelerate bitsandbytes
 ```
-7. To troubleshoot installs try the below (all must succeed). Xformers should mostly all be available.
+6. To troubleshoot installs try the below (all must succeed). Xformers should mostly all be available.
 ```bash
 nvcc
 python -m xformers.info
 python -m bitsandbytes
 ```
+7. If you get errors, try the below first, then go back to step 1:
+```bash
+pip install --upgrade pip
+```
 
+</details>
 ## 📜 Documentation
 - Go to our [Wiki page](https://github.com/unslothai/unsloth/wiki) for saving to GGUF, checkpointing, evaluation and more!
 - We support Huggingface's TRL, Trainer, Seq2SeqTrainer or even Pytorch code!

install.sh

@@ -0,0 +1,114 @@
+#!/bin/bash
+
+# Function to get PyTorch version if installed
+get_pytorch_version () {
+    if python -c "import torch" &> /dev/null; then
+        PYTORCH_VERSION=$(python -c "import torch; print(torch.__version__)")
+        echo $PYTORCH_VERSION
+    else
+        echo "not installed"
+    fi
+}
+
+# Function to get GPU architecture
+get_gpu_type () {
+    GPU_MAJOR_VERSION=$(python -c "import torch; print(torch.cuda.get_device_capability()[0])")
+    if [[ "$GPU_MAJOR_VERSION" -ge 8 ]]; then
+        echo "ampere"
+    else
+        echo ""
+    fi
+}
+
+# Function to install packages via Conda
+conda_install_packages () {
+    conda create --name unsloth_env python=3.10 -y
+    CONDA_BASE=$(conda info --base)
+    CONDA_SH="$CONDA_BASE/etc/profile.d/conda.sh"
+    if [[ -f "$CONDA_SH" ]]; then
+        echo "Sourcing Conda from $CONDA_SH"
+        source "$CONDA_SH"
+    else
+        echo "Unable to locate conda.sh at $CONDA_SH. Please ensure Conda is properly installed."
+        exit 1
+    fi
+    conda activate unsloth_env
+    conda install pytorch cudatoolkit=${CUDA_TAG} torchvision torchaudio pytorch-cuda=${CUDA_TAG} -c pytorch -c nvidia -y
+    conda install xformers -c xformers -y
+    pip install bitsandbytes
+    pip install "unsloth[conda] @ git+https://github.com/unslothai/unsloth.git"
+}
+
+# Function to install packages via Pip
+pip_install_packages () {
+    pip install --upgrade --force-reinstall --no-cache-dir torch==${PYTORCH_CORE_VERSION}+${CUDA_TAG} triton --index-url https://download.pytorch.org/whl/${CUDA_TAG}
+    if [[ "$PYTORCH_VERSION_TAG" == "torch210" ]]; then
+        pip install "unsloth[${CUDA_TAG}${GPU_TYPE:+-$GPU_TYPE}] @ git+https://github.com/unslothai/unsloth.git"
+    elif [[ "$PYTORCH_VERSION_TAG" == "torch221" ]]; then
+        pip install "unsloth[colab-221] @ git+https://github.com/unslothai/unsloth.git"
+        if [[ "$CUDA_TAG" == "cu118" ]]; then
+            pip install --no-deps packaging ninja einops flash-attn xformers trl peft accelerate bitsandbytes
+        else
+            pip install --no-deps xformers trl peft accelerate bitsandbytes
+        fi
+    else
+        pip install "unsloth[${CUDA_TAG}${GPU_TYPE:+-$GPU_TYPE}-$PYTORCH_VERSION_TAG] @ git+https://github.com/unslothai/unsloth.git"
+    fi
+}
+
+# Check if conda is installed
+if type conda &> /dev/null; then
+    echo "Anaconda/Miniconda is installed, proceeding with Conda installation."
+
+    # Determine CUDA version
+    CUDA_VERSION=$(nvcc --version | grep "release" | sed 's/.*release //' | sed 's/,.*//')
+    echo "CUDA version detected: $CUDA_VERSION"
+
+    # Choose the right tag for pytorch-cuda
+    # TODO: This is janky, we should find a better way to do this
+    cuda_version_value=$(echo "$CUDA_VERSION" | bc)
+    if [ "$(echo "$cuda_version_value < 12" | bc -l)" -eq 1 ]; then
+        CUDA_TAG="11.8"
+    else
+        CUDA_TAG="12.1"
+    fi
+
+    conda_install_packages
+
+# If conda is not installed, use pip
+else
+    echo "Anaconda/Miniconda is not installed, checking for CUDA and proceeding with Pip installation."
+
+    # Check if CUDA is available
+    if type nvcc &> /dev/null; then
+        CUDA_VERSION=$(nvcc --version | grep "release" | sed 's/.*release //' | sed 's/,.*//')
+        echo "CUDA version detected: $CUDA_VERSION"
+        PYTORCH_VERSION=$(get_pytorch_version)
+        echo "PyTorch version detected: $PYTORCH_VERSION"
+        GPU_TYPE=$(get_gpu_type)
+        if [[ $GPU_TYPE == "ampere" ]]; then
+            echo "Ampere or newer architecture detected. Proceeding with ampere specific installation."
+        else
+            echo "Older GPU architecture detected. Proceeding with non-ampere specific installation."
+        fi
+        # Define CUDA tag based on CUDA version
+        if [[ "$CUDA_VERSION" == "11.8" ]]; then
+            CUDA_TAG="cu118"
+        elif [[ "$CUDA_VERSION" == "12.1" ]]; then
+            CUDA_TAG="cu121"
+        else
+            echo "Unsupported CUDA version for Pip installation. Exiting."
+            exit 1
+        fi
+
+        # Extract PyTorch version (ignoring any suffix)
+        PYTORCH_CORE_VERSION=$(echo $PYTORCH_VERSION | cut -d'+' -f1)
+        PYTORCH_VERSION_TAG="torch${PYTORCH_CORE_VERSION//./}"
+
+        pip_install_packages
+
+    else
+        echo "CUDA not detected. Pip installation requires CUDA. Exiting."
+        exit 1
+    fi
+fi

pyproject.toml

@@ -161,7 +161,7 @@ colab-ampere-torch220 = [
     "ninja",
     "flash-attn",
 ]
-colab-new = [
+colab-221 = [
     "tyro",
     "transformers>=4.38.2",
     "datasets>=2.16.0",