Depth Estimation
Transformers
Safetensors
English
qwen3_vl
image-text-to-text
vision-language-model
3d-vision
multimodal
Instructions to use JonnyYu828/DepthVLM-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JonnyYu828/DepthVLM-4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("depth-estimation", model="JonnyYu828/DepthVLM-4B")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("JonnyYu828/DepthVLM-4B") model = AutoModelForImageTextToText.from_pretrained("JonnyYu828/DepthVLM-4B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86b464b0287185afb1baaf7c38546490aa6dd3097cf10f6ed72ffe63d4450daf
- Size of remote file:
- 9.72 GB
- SHA256:
- fa4d66ea78f8fc49bf31aa8c7e7aa91da3f71e328885d6c3a62a9fd8ca97585e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.