Other
Transformers
Safetensors
PyTorch
English
vision-language-action
humanoid-robotics
telepathy
multimodal
robotics-control
lora
Instructions to use Veltraxor/Sigma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Veltraxor/Sigma with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Veltraxor/Sigma", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "sigma_env": "sigma.env", | |
| "output_dir": "/workspace/storage/sigma_lora_out", | |
| "base_model_id": "lerobot/pi05_base", | |
| "load_in_4bit": true, | |
| "torch_dtype": "bf16", | |
| "dataset_id": null, | |
| "split": "train", | |
| "data_dir": "/workspace/storage/sigma_pickplace", | |
| "hf_data_repo": "Veltraxor/Sigma", | |
| "hf_data_subdir": "storage/sigma_pickplace", | |
| "prefer_hf_shards": false, | |
| "auto_prune_hf_cache": false, | |
| "hf_cache_keep_latest": 1, | |
| "hf_cache_dir": null, | |
| "num_workers": 4, | |
| "epochs": 3, | |
| "batch_size": 2, | |
| "grad_accum": 8, | |
| "lr": 0.0002, | |
| "warmup_ratio": 0.03, | |
| "weight_decay": 0.0, | |
| "max_steps": -1, | |
| "seed": 42, | |
| "log_every": 10, | |
| "alpha_a": 1.0, | |
| "alpha_b": 1.0, | |
| "alpha_c": 1.0, | |
| "lambda_sem": 1.0, | |
| "lambda_intent": 0.8, | |
| "lambda_tau": 0.03, | |
| "beta_mi": 0.1, | |
| "eta_var": 0.2, | |
| "hard_mining_ratio": 0.3, | |
| "hard_mining_lambda": 1.0, | |
| "loss_warmup_ratio": 0.6, | |
| "lambda_sem_start": 0.1, | |
| "lambda_intent_start": 0.1, | |
| "max_grad_norm": 1.0, | |
| "lora_r": 16, | |
| "lora_alpha": 32, | |
| "lora_dropout": 0.05, | |
| "target_modules": [ | |
| "q_proj", | |
| "k_proj", | |
| "v_proj", | |
| "o_proj" | |
| ], | |
| "train_base_lora": false | |
| } |