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  1. README.md +4 -4
  2. config.json +4 -4
  3. dataset_statistics.npy +3 -0
  4. model.safetensors +2 -2
README.md CHANGED
@@ -7,9 +7,9 @@ tags:
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  - pytorch
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  ---
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- # Octo-Base PyTorch Model
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- This is the octo-base model converted to PyTorch format.
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  ## Model Description
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@@ -19,7 +19,7 @@ Octo is a generalist robot policy trained on diverse robot manipulation tasks.
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  - **Original JAX Implementation**: [octo-models/octo](https://github.com/octo-models/octo)
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  - **Original Pytorch Implementation**: [emb-ai/octo-pytorch](https://github.com/emb-ai/octo-pytorch)
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  - **lil'km Implementation**: [s1lent4gnt/octo-pytorch](https://github.com/s1lent4gnt/octo-pytorch)
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- - **Model Size**: octo-base
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  ## Usage
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@@ -60,7 +60,7 @@ model = OctoModel.from_pretrained('lilkm/octo-small-test')
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  ### Model Architecture
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- - **Transformer**: 12 layers, 768 dim, 12 heads
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  - **Vision Encoder**: Custom CNN (SmallStem16)
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  - **Language Encoder**: T5-Base
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  - **Action Head**: Diffusion policy with 4 action steps
 
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  - pytorch
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  ---
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+ # Octo-Small PyTorch Model
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+ This is the octo-small model converted to PyTorch format.
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  ## Model Description
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  - **Original JAX Implementation**: [octo-models/octo](https://github.com/octo-models/octo)
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  - **Original Pytorch Implementation**: [emb-ai/octo-pytorch](https://github.com/emb-ai/octo-pytorch)
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  - **lil'km Implementation**: [s1lent4gnt/octo-pytorch](https://github.com/s1lent4gnt/octo-pytorch)
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+ - **Model Size**: octo-small
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  ## Usage
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  ### Model Architecture
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+ - **Transformer**: 12 layers, 384 dim, 6 heads
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  - **Vision Encoder**: Custom CNN (SmallStem16)
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  - **Language Encoder**: T5-Base
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  - **Action Head**: Diffusion policy with 4 action steps
config.json CHANGED
@@ -1,10 +1,10 @@
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  {
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  "model_type": "octo",
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- "model_name": "octo-base",
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- "token_embedding_size": 768,
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  "num_layers": 12,
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- "num_heads": 12,
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- "mlp_dim": 3072,
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  "max_horizon": 10,
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  "repeat_task_tokens": true,
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  "action_horizon": 4,
 
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  {
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  "model_type": "octo",
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+ "model_name": "octo-small",
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+ "token_embedding_size": 384,
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  "num_layers": 12,
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+ "num_heads": 6,
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+ "mlp_dim": 1536,
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  "max_horizon": 10,
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  "repeat_task_tokens": true,
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  "action_horizon": 4,
dataset_statistics.npy ADDED
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