Robotics
Transformers
Safetensors
qwen2_5_vl
image-text-to-text
vision-language-action-model
vision-language-model
text-generation-inference
Instructions to use InternRobotics/RoboInter-VLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InternRobotics/RoboInter-VLM with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("InternRobotics/RoboInter-VLM") model = AutoModelForImageTextToText.from_pretrained("InternRobotics/RoboInter-VLM") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| base_model: | |
| - Qwen/Qwen2.5-VL-7B-Instruct | |
| tags: | |
| - robotics | |
| - vision-language-action-model | |
| - vision-language-model | |
| library_name: transformers | |
| # Collection Metadata (Referencing InternRobotics/VLN-PE style) | |
| repo: InternRobotics/RoboInter-VLM | |
| type: "checkpoint-collection" | |
| description: "RoboInterVLM flagship checkpoint (Qwen2.5-VL-7B) fine-tuned on RoboInter-VQA." | |
| checkpoints: | |
| - name: RoboInter-VLM | |
| notes: "Flagship Qwen2.5-VL-7B backbone" | |