Robotics
Transformers
Safetensors
English
eo1
feature-extraction
Robot Control
Generalist robot policies
VLA
Embodied AI
Unified Model
multimodal
large embodied model
custom_code
Instructions to use IPEC-COMMUNITY/EO-1-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IPEC-COMMUNITY/EO-1-3B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("IPEC-COMMUNITY/EO-1-3B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| # Copyright 2025 EO-Robotics Team. All rights reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| from transformers.configuration_utils import PretrainedConfig | |
| from transformers.models.qwen2_5_vl.configuration_qwen2_5_vl import ( | |
| Qwen2_5_VLTextConfig, | |
| Qwen2_5_VLVisionConfig, | |
| ) | |
| class EO1VisionFlowMatchingConfig(PretrainedConfig): | |
| model_type = "eo1" | |
| sub_configs = {"vision_config": Qwen2_5_VLVisionConfig, "text_config": Qwen2_5_VLTextConfig} | |
| keys_to_ignore_at_inference = ["past_key_values"] | |
| def __init__( | |
| self, | |
| text_config=None, | |
| vision_config=None, | |
| image_token_id=151655, | |
| video_token_id=151656, | |
| action_chunk_size=50, | |
| max_action_dim=32, | |
| num_denoise_steps=10, | |
| action_act="linear", | |
| num_action_layers=2, | |
| state_token_id=151669, | |
| action_token_id=151666, | |
| action_pass_id=151672, | |
| **kwargs, | |
| ): | |
| if isinstance(vision_config, dict): | |
| self.vision_config = self.sub_configs["vision_config"](**vision_config) | |
| elif vision_config is None: | |
| self.vision_config = self.sub_configs["vision_config"]( | |
| hidden_size=1280, | |
| out_hidden_size=2048, | |
| tokens_per_second=2, | |
| ) | |
| if isinstance(text_config, dict): | |
| self.text_config = self.sub_configs["text_config"](**text_config) | |
| elif text_config is None: | |
| self.text_config = self.sub_configs["text_config"](**kwargs) | |
| self.image_token_id = image_token_id | |
| self.video_token_id = video_token_id | |
| self.state_token_id = state_token_id | |
| self.action_token_id = action_token_id | |
| self.action_pass_id = action_pass_id | |
| self.action_chunk_size = action_chunk_size | |
| self.max_action_dim = max_action_dim | |
| self.num_denoise_steps = num_denoise_steps | |
| self.action_act = action_act | |
| self.num_action_layers = num_action_layers | |
| super().__init__(**kwargs) | |
| EO1VisionFlowMatchingConfig.register_for_auto_class() | |