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@azazdeaz
Last active January 3, 2026 11:04
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finetuning_gr00t
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "view-in-github"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/azazdeaz/9b3f1cfe5eb7cb61735d6e7c2ce64036/training-smolvla.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "PolVM_movEvp",
"outputId": "cd4ff80c-7555-4fad-d182-c92c47225030"
},
"outputs": [],
"source": [
"# !wandb login"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "nAIoNcgkgYFz",
"outputId": "dc93aefa-8016-41ab-dc6c-f9e7d23736ff"
},
"outputs": [],
"source": [
"!git clone --recurse-submodules https://github.com/azazdeaz/Isaac-GR00T\n",
"!cd Isaac-GR00T/ && uv sync --python 3.10 && uv pip install -e .\n",
"!cd Isaac-GR00T/scripts/lerobot_conversion/ && uv sync && uv pip install -e ."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "0Chgh-NW7x3c",
"outputId": "978f55cb-7e28-42f1-cebc-85d025ce0570"
},
"outputs": [],
"source": [
"!cd Isaac-GR00T/scripts/lerobot_conversion/ && uv sync && uv pip install -e .\n",
"!cd Isaac-GR00T/scripts/lerobot_conversion/ && \\\n",
" uv run python convert_v3_to_v2.py \\\n",
" --repo-id azazdeaz/record-test \\\n",
" --root /content/dataset/azazdeaz/record-test"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "8tq-QvzB8nxt"
},
"outputs": [],
"source": [
"!cp Isaac-GR00T/examples/SO100/modality.json /content/dataset/azazdeaz/record-test/azazdeaz/record-test/meta/modality.json"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "EI1ja0qH_Jb5",
"outputId": "6f8cd686-34a9-4c64-c081-b72cbda4e013"
},
"outputs": [],
"source": [
"!cd Isaac-GR00T/ && \\\n",
" CUDA_VISIBLE_DEVICES=0 \\\n",
" uv run torchrun --nproc_per_node=1 --master_port=29500 \\\n",
" gr00t/experiment/launch_finetune.py \\\n",
" --base_model_path nvidia/GR00T-N1.6-3B \\\n",
" --dataset_path /content/dataset/azazdeaz/record-test/azazdeaz/record-test/ \\\n",
" --modality_config_path examples/SO100/so100_config.py \\\n",
" --embodiment_tag NEW_EMBODIMENT \\\n",
" --num_gpus 1 \\\n",
" --output_dir /content/so100_finetune \\\n",
" --save_steps 1000 \\\n",
" --save_total_limit 5 \\\n",
" --max_steps 10000 \\\n",
" --warmup_ratio 0.05 \\\n",
" --weight_decay 1e-5 \\\n",
" --learning_rate 1e-4 \\\n",
" # --use_wandb \\\n",
" --global_batch_size 32 \\\n",
" --color_jitter_params brightness 0.3 contrast 0.4 saturation 0.5 hue 0.08 \\\n",
" --dataloader_num_workers 4"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Q8Sn2wG4wldo"
},
"source": [
"## Weights & Biases login\n",
"This cell logs you into Weights & Biases (wandb) to enable experiment tracking and logging."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "x7CXXrgufg2R"
},
"source": [
"## Install SmolVLA dependencies"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "UakszYwVfg2S"
},
"source": [
"## Login into Hugging Face Hub\n",
"Now after training is done login into the Hugging Face hub and upload the last checkpoint"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "8yu5khQGIHi6",
"outputId": "7d26fb8c-7aea-4c07-dbf5-4cb9e82f75c1"
},
"outputs": [],
"source": [
"!huggingface-cli login"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "zFMLGuVkH7UN",
"outputId": "12ec03b7-9ccb-483e-d37e-7a2a8992576f"
},
"outputs": [],
"source": [
"!huggingface-cli upload ${HF_USER}/test_grootN1_6 \\\n",
" /content/lerobot/outputs/train/my_smolvla/checkpoints/last/pretrained_model"
]
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"gpuType": "A100",
"include_colab_link": true,
"name": "training-SO101-gr00t.ipynb",
"provenance": []
},
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.12"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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