Robotics
Transformers
Safetensors
qwen2
text-generation
text-generation-inference

Update Paper Link and Add Github Link

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by nielsr HF Staff - opened
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  1. README.md +8 -8
README.md CHANGED
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  ---
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- library_name: transformers
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- pipeline_tag: robotics
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- license: apache-2.0
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- datasets:
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- - homebrewltd/Pick-Place-Table-Reasoning-local-pos-v0.2
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  base_model:
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  - deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
 
 
 
 
 
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  ---
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  # AlphaSpace-1.5B
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  ## Introduction
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- **"AlphaSpace:** ([Paper](https://huggingface.co/papers/2503.07111)), a novel methodology designed to enhance the spatial reasoning capabilities of language models for robotic manipulation in 3D Cartesian space. AlphaSpace employs a hierarchical semantics-based tokenization strategy that encodes spatial information at both coarse and fine-grained levels. Our approach represents objects with their attributes, positions, and height information through structured tokens, enabling precise spatial reasoning without relying on traditional vision-based embeddings. This approach enables LLMs to accurately manipulate objects by positioning them at specific [x, y, z] coordinates.
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  ## Model Details
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  * Model architecture: [Deepseek-R1-Distil-Qwen-1.5B Instruct](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B)
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  | **Precision** | bf16 |
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  ## Citation
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- - arxiv.org/abs/2503.07111
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- - arxiv.org/abs/2503.18769
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  ## More Information
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  * Contact the authors at [email protected], [email protected], [email protected] for further details.
 
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  ---
 
 
 
 
 
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  base_model:
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  - deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
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+ datasets:
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+ - homebrewltd/Pick-Place-Table-Reasoning-local-pos-v0.2
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+ library_name: transformers
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+ license: apache-2.0
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+ pipeline_tag: robotics
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  ---
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  # AlphaSpace-1.5B
 
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  ## Introduction
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+ **"AlphaSpace:** ([Paper](https://huggingface.co/papers/2503.18769)), a novel methodology designed to enhance the spatial reasoning capabilities of language models for robotic manipulation in 3D Cartesian space. AlphaSpace employs a hierarchical semantics-based tokenization strategy that encodes spatial information at both coarse and fine-grained levels. Our approach represents objects with their attributes, positions, and height information through structured tokens, enabling precise spatial reasoning without relying on traditional vision-based embeddings. This approach enables LLMs to accurately manipulate objects by positioning them at specific [x, y, z] coordinates.
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+ Code: https://github.com/AlanDao/AlphaSpace
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  ## Model Details
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  * Model architecture: [Deepseek-R1-Distil-Qwen-1.5B Instruct](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B)
 
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  | **Precision** | bf16 |
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  ## Citation
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+ - https://arxiv.org/abs/2503.18769
 
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  ## More Information
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  * Contact the authors at [email protected], [email protected], [email protected] for further details.