Instructions to use pigProfessional/smolvla_stack_green with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use pigProfessional/smolvla_stack_green 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=pigProfessional/smolvla_stack_green \ --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=pigProfessional/smolvla_stack_green - Notebooks
- Google Colab
- Kaggle
Download tokenizer/tokenizer_config.json from pigProfessional/smolvla_stack_green: direct link, hf CLI and curl.
- Browser
- Download file 838 Bytes
-
https://huggingface.co/pigProfessional/smolvla_stack_green/resolve/main/tokenizer/tokenizer_config.json
- Command line
-
hf download hf://pigProfessional/smolvla_stack_green/tokenizer/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/pigProfessional/smolvla_stack_green/resolve/main/tokenizer/tokenizer_config.json
838 Bytes
| { | |
| "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 | |
| } | |