Instructions to use maedmatt/DREAM_SmolVLA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use maedmatt/DREAM_SmolVLA with LeRobot:
# See https://github.com/huggingface/lerobot?tab=readme-ov-file#installation for more details git clone https://github.com/huggingface/lerobot.git cd lerobot pip install -e .[smolvla]
# Launch finetuning on your dataset python lerobot/scripts/train.py \ --policy.path=maedmatt/DREAM_SmolVLA \ --dataset.repo_id=lerobot/svla_so101_pickplace \ --batch_size=64 \ --steps=20000 \ --output_dir=outputs/train/my_smolvla \ --job_name=my_smolvla_training \ --policy.device=cuda \ --wandb.enable=true
# Run the policy using the record function python -m lerobot.record \ --robot.type=so101_follower \ --robot.port=/dev/ttyACM0 \ # <- Use your port --robot.id=my_blue_follower_arm \ # <- Use your robot id --robot.cameras="{ front: {type: opencv, index_or_path: 8, width: 640, height: 480, fps: 30}}" \ # <- Use your cameras --dataset.single_task="Grasp a lego block and put it in the bin." \ # <- Use the same task description you used in your dataset recording --dataset.repo_id=HF_USER/dataset_name \ # <- This will be the dataset name on HF Hub --dataset.episode_time_s=50 \ --dataset.num_episodes=10 \ --policy.path=maedmatt/DREAM_SmolVLA - Notebooks
- Google Colab
- Kaggle
File size: 838 Bytes
826333f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | {
"add_prefix_space": false,
"backend": "tokenizers",
"bos_token": "<|im_start|>",
"clean_up_tokenization_spaces": false,
"end_of_utterance_token": "<end_of_utterance>",
"eos_token": "<end_of_utterance>",
"errors": "replace",
"fake_image_token": "<fake_token_around_image>",
"global_image_token": "<global-img>",
"image_token": "<image>",
"is_local": false,
"legacy": false,
"model_max_length": 8192,
"model_specific_special_tokens": {
"end_of_utterance_token": "<end_of_utterance>",
"fake_image_token": "<fake_token_around_image>",
"global_image_token": "<global-img>",
"image_token": "<image>"
},
"pad_token": "<|im_end|>",
"processor_class": "SmolVLMProcessor",
"tokenizer_class": "GPT2Tokenizer",
"truncation_side": "left",
"unk_token": "<|endoftext|>",
"vocab_size": 49152
}
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