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chore: Regenerate all playbooks

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33
nvidia/pytorch-fine-tune/README.md
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@ -40,13 +40,32 @@ ALl files required for finetuning are included.
## Instructions
## Step 1. Pull the latest Pytorch container
## Step 1. Configure Docker permissions
To easily manage containers without sudo, you must be in the `docker` group. If you choose to skip this step, you will need to run Docker commands with sudo.
Open a new terminal and test Docker access. In the terminal, run:
```bash
docker ps
```
If you see a permission denied error (something like `permission denied while trying to connect to the Docker daemon socket`), add your user to the docker group:
```bash
sudo usermod -aG docker $USER
```
> **Warning**: After running usermod, you must log out and log back in to start a new
> session with updated group permissions.
## Step 2. Pull the latest Pytorch container
```bash
docker pull nvcr.io/nvidia/pytorch:25.09-py3
```
## Step 2. Launch Docker
## Step 3. Launch Docker
```bash
docker run --gpus all -it --rm --ipc=host \
@ -54,15 +73,18 @@ docker run --gpus all -it --rm --ipc=host \
-v ${PWD}:/workspace -w /workspace \
nvcr.io/nvidia/pytorch:25.09-py3
-v $HOME/.cache/huggingface:/root/.cache/huggingface \
-v ${PWD}:/workspace -w /workspace \
nvcr.io/nvidia/pytorch:25.09-py3
```
## Step 3. Install dependencies inside the contianer
## Step 4. Install dependencies inside the contianer
```bash
pip install transformers peft datasets "trl==0.19.1" "bitsandbytes==0.48"
```
## Step 4: authenticate with huggingface
## Step 5: authenticate with huggingface
```bash
huggingface-cli login
@ -70,7 +92,7 @@ huggingface-cli login
##<Enter n for git credential>
```
To run LoRA on Llama3 use the following command:
To run LoRA on Llama3-8B use the following command:
```bash
python Llama3_8B_LoRA_finetuning.py
@ -80,6 +102,7 @@ To run qLoRA finetuning on llama3-70B use the following command:
```bash
python Llama3_70B_qLoRA_finetuning.py
```
To run full finetuning on llama3-3B use the following command:
```bash
python Llama3_3B_full_finetuning.py