ur10e_smolvla_2 is an open-source robotics policy model for imitation learning, designed for use with the LeRobot library. Below are 23 other ai apps with similar functionality to Ur10e Smolvla 2, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
ur10e_smolvla_1 is an open-source robotics policy model designed for controlling UR10e robots via the LeRobot framework. It supports multimodal inputs and enables researchers to train, fine-tune, and deploy advanced robot control policies. The model is suitable for robotics research and practical applications in automation.
ur10e_smolvla_3 is an open-source robotics policy model designed for controlling UR10e robotic arms. It integrates with LeRobot and is intended for robotics developers and researchers seeking customizable, locally deployable control policies.
smolvla_so101_t2_v3 is an open-source robotics policy model for imitation learning, distributed via Hugging Face. It enables researchers and developers to train, evaluate, and deploy manipulation policies for robotic systems, supporting fine-tuning and integration with robotics frameworks.
smolvla_so101_t1_v3 is an open-source robotics policy model for imitation learning and control tasks. It integrates with LeRobot and supports training, evaluation, and deployment for robotics research and development.
smolvla_mir1_v2 is an open-source AI model focused on robotics and policy learning. It supports integration with robotics frameworks and can be fine-tuned for custom tasks, making it ideal for robotics researchers and developers.
This Hugging Face repository offers an open-source robotics policy model designed for use in robotics research and development. The model can be integrated with Python and supports local inference, making it suitable for custom robotics applications. Distributed under the Apache-2.0 license.
Smolvla DS3 1B1O FV Removeidle Rand40 is a model available on Hugging Face, associated with the robotics domain. The model is referenced in connection with LeRobot, and instructions are provided for using it with this library. The evidence indicates that users can clone the LeRobot repository, install it with a specific option for smolvla, and launch finetuning of the model on a dataset using a provided script. The example given uses a dataset identified as lerobot/svla_so101_pickplace, and allows configuration of batch size, training steps, output directory, job name, device, and integration with wandb for tracking. The model is distributed under the Apache 2.0 license, and is available in the safetensors format. There is also a reference to arxiv: 2506.01844, suggesting a related publication. The evidence does not provide further details about the model's specific capabilities, intended audience beyond robotics and LeRobot users, or additional features. Pricing information is not mentioned, but the Apache 2.0 license indicates it is open source. No claims are made about integrations beyond LeRobot, nor about supported platforms other than those implied by the use of Python scripts and CUDA devices.
smolvla_DS3_1B1O_FV_removeidle_rand60 is an open-source AI model focused on robotics and policy learning. It supports integration with robotics frameworks and can be fine-tuned for custom tasks, making it ideal for robotics researchers and developers.
smolvla_so101_t2_v2 is an open-source robotics model designed for use with the LeRobot library. It supports fine-tuning on custom datasets and deployment in simulation environments, making it suitable for robotics engineers and researchers.
smolvla_so101_cube_put_20260710_frozen is an open-source robotics policy model designed for cube manipulation tasks. It is compatible with the LeRobot library and can be used for research, training, and evaluation in robotics environments. The model is distributed via Hugging Face for local use and further experimentation.
smolvla_so101_cube_put_20260710 is an open-source robotics policy model for cube placement tasks, designed for use with the LeRobot framework. It allows researchers and engineers to train, fine-tune, and deploy robotics policies using open weights.
smolvla_DS1_1B1O_FF_removeidle_rand40 is an open-source robotics policy model designed for use with the LeRobot framework. It enables developers to implement, fine-tune, and deploy policy models for robotic control tasks. The model is distributed under the Apache-2.0 license and integrates with Python-based robotics workflows.
smolvla_p3_redcube_merged is an open-source robotics policy model designed for manipulation and control tasks. It is suitable for robotics researchers and developers seeking to implement or fine-tune policies for robotic arms and similar systems.
smolvla-so101-candy-33c62cfe is an open-source robotics policy model designed for use with the LeRobot framework and similar robotics platforms. It enables researchers and developers to train, evaluate, and deploy robotic control policies using open weights and local inference.
smolvla_DS1_1B1O_FF_removeidle_rand80 is an open-source robotics policy model distributed via Hugging Face. It is designed for use with the LeRobot framework and supports fine-tuning and deployment in robotics research. The model is accessible via API and CLI, with open weights for customization and experimentation.
so101_smolvla_model is an open-source robotics policy model designed for imitation learning and manipulation tasks, compatible with the LeRobot framework. It supports fine-tuning, Colab integration, and is aimed at robotics researchers and developers seeking customizable policy models.
smolvla_so101_v5_30k is an open-source robotics policy model for controlling SO101 robots, compatible with the LeRobot library and Python. It is designed for robotics developers and researchers to implement imitation learning and automate robotic tasks. The model is distributed via Hugging Face.
smolvla_so101_cube_put_take_20260710 is an open-source robotics policy model designed for cube put-and-take tasks, compatible with the LeRobot framework. It allows robotics researchers to run, fine-tune, and evaluate manipulation policies in simulation or on real robots.
smolvla_dohyun_policy is an open-source robotics policy model designed for use with the LeRobot framework. It provides pretrained weights and supports fine-tuning for various robotic control tasks. Ideal for robotics researchers and developers working on machine learning for robotics.
smolvla_DS1_1B1O_FF_removeidle_rand20 is an open-source reinforcement learning model designed for robotics applications using the LeRobot framework. It offers model checkpoints and fine-tuning capabilities for researchers and developers in robotics and AI.
smolvla_so101_cube_put_20260710_frozen_200k is an open-source robotics policy model designed for cube manipulation and pick-and-place tasks. It integrates with LeRobot and is suitable for researchers and developers working on robotic control and imitation learning.
Smolvla So101 Candy 63d2cc57 is a model hosted on Hugging Face and associated with the Qualia Robotics organization. The model is referenced in connection with robotics applications, as indicated by its integration instructions for use with the LeRobot library. Users are provided with commands for fine-tuning the model on custom datasets and for running the policy using specific scripts, suggesting its intended use in training and deploying robotics policies. The documentation points to a repository and provides sample commands for cloning and installing the LeRobot library, as well as for launching fine-tuning and running the policy, which implies that the model is designed to be used within Python-based robotics workflows. The model card references the arXiv preprint 2506.01844, indicating that there is a research publication associated with the model, although no further details about its contents or capabilities are provided in the evidence. The license is explicitly stated as Apache-2.0, confirming that the model is available under an open-source license. The evidence also notes that the model is available in the EU region and can be used with various libraries, inference providers, notebooks, and local applications, though specific details about these integrations are not elaborated. No information is provided about the specific features, architecture, or intended user base beyond its association with robotics and compatibility with LeRobot. There are no explicit claims about supported input types, performance, or other technical specifications. Pricing details are not mentioned, but the Apache-2.0 license suggests it is free to use under open-source terms. Overall, Smolvla So101 Candy 63d2cc57 is positioned as an open-source model for robotics-related tasks, with available integration instructions for Python-based robotics libraries.
smolvla_white_in_blue_circle is an open-source AI model for robotics control and policy learning, distributed with model weights and instructions for use with the LeRobot library. It is intended for robotics researchers and developers building control systems.
