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  # RDT-1B
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- RDT-1B is a 1B-parameter (largest to date) imitation learning Diffusion Transformer pre-trained on 1M+ (largest to date) multi-robot episodes. Given a language instruction and 3-view RGB image observations, RDT can predict the next
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  64 robot actions. RDT is inherently compatible with almost all kinds of modern mobile manipulators, from single-arm to dual-arm, joint to EEF, pos. to vel., and even with a mobile chassis.
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- <!-- ## Model Details
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- <!-- ### Model Description
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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- -->
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-
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- ### Model Sources
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- <!-- Provide the basic links for the model. -->
 
 
 
 
 
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  - **Repository:** [More Information Needed]
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  - **Paper :** [More Information Needed]
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  ## Uses
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- RDT-1B supports finetuning on custom dataset, deploying and inferencing on real-robots, and pre-training with large scale datasets.
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  Please refer to [our repository](https://github.com/GeneralEmbodiedSystem/RoboticsDiffusionTransformer/blob/main/docs/pretrain.md) for all the above guides.
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  ---
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  # RDT-1B
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+ RDT-1B is a 1B-parameter imitation learning Diffusion Transformer pre-trained on 1M+ multi-robot episodes. Given a language instruction and 3-view RGB image observations, RDT can predict the next
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  64 robot actions. RDT is inherently compatible with almost all kinds of modern mobile manipulators, from single-arm to dual-arm, joint to EEF, pos. to vel., and even with a mobile chassis.
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+ All the code and model weights are licensed under MIT license.
 
 
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+ Please refer to our [project page](), [github repository]() and [paper]() for more information.
 
 
 
 
 
 
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+ ## Model Details
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+ - **Developed by** Thu-ml team
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+ - **License:** MIT
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+ - **Pretrain dataset:** [More Information Needed]
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+ - **Finetune dataset:** [More Information Needed]
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  - **Repository:** [More Information Needed]
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  - **Paper :** [More Information Needed]
 
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  ## Uses
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+ RDT-1B supports finetuning and pre-training on custom dataset, as well as deploying and inferencing on real-robots.
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  Please refer to [our repository](https://github.com/GeneralEmbodiedSystem/RoboticsDiffusionTransformer/blob/main/docs/pretrain.md) for all the above guides.
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