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README.md

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+---
+license: mit
+tags:
+- robotics
+- imitation-learning
+- octo
+- pytorch
+---
+
+# Octo-Base PyTorch Model
+
+This is the octo-base model converted to PyTorch format.
+
+## Model Description
+
+Octo is a generalist robot policy trained on diverse robot manipulation tasks.
+
+- **Paper**: [Octo: An Open-Source Generalist Robot Policy](https://arxiv.org/pdf/2405.12213)
+- **Original JAX Implementation**: [octo-models/octo](https://github.com/octo-models/octo)
+- **Original Pytorch Implementation**: [emb-ai/octo-pytorch](https://github.com/emb-ai/octo-pytorch)
+- **lil'km Implementation**: [s1lent4gnt/octo-pytorch](https://github.com/s1lent4gnt/octo-pytorch)
+- **Model Size**: octo-base
+
+## Usage
+
+### Loading the pretrained model
+
+```python
+import torch
+from safetensors.torch import load_file
+import json
+from octo_pytorch.model import OctoModel
+from octo_pytorch.model.configuration_octo import OctoConfig
+
+# Load config
+with open('config.json', 'r') as f:
+    config_dict = json.load(f)
+
+# Initialize model configuration
+config = OctoConfig(model_name=config_dict['model_name'])
+
+# Initialize model
+model = OctoModel(config)
+
+# Load weights (T5 encoder weights will be loaded automatically from HuggingFace Hub)
+state_dict = load_file('model.safetensors')
+model.load_state_dict(state_dict, strict=False)  # strict=False because T5 weights are not in the file
+```
+
+### Alternative: Direct loading from HuggingFace Hub
+
+```python
+from octo_pytorch.model import OctoModel
+
+# Load model directly from HuggingFace Hub
+model = OctoModel.from_pretrained('lilkm/octo-small-test')
+```
+
+**Note**: The T5-base language encoder weights are not included in this upload to save space. They will be automatically downloaded from HuggingFace Hub when you initialize the model.
+
+### Model Architecture
+
+- **Transformer**: 12 layers, 768 dim, 12 heads
+- **Vision Encoder**: Custom CNN (SmallStem16)
+- **Language Encoder**: T5-Base
+- **Action Head**: Diffusion policy with 4 action steps
+- **Max Horizon**: 10 timesteps
+- **Action Dimension**: 7
+
+## Files
+
+- `model.safetensors`: Model weights in safetensors format
+- `config.json`: Model configuration
+- `dataset_statistics.npy`: Dataset statistics used for normalization (if available)
+
+## Citation
+
+If you use this model, please cite:
+
+```bibtex
+@article{octo_2023,
+    title={Octo: An Open-Source Generalist Robot Policy},
+    author={Octo Model Team et al.},
+    journal={arXiv preprint arXiv:2405.12213},
+    year={2024}
+}
+```

config.json

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+{
+  "model_type": "octo",
+  "model_name": "octo-base",
+  "token_embedding_size": 768,
+  "num_layers": 12,
+  "num_heads": 12,
+  "mlp_dim": 3072,
+  "max_horizon": 10,
+  "repeat_task_tokens": true,
+  "action_horizon": 4,
+  "action_dim": 7,
+  "diffusion_steps": 20
+}

model.safetensors

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+oid sha256:f8c8e2f7c7b97b889d413006801ea351cb2213060a69b830ed7b2f83abbceaeb
+size 371352224