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
File size: 466 Bytes
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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"
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