Image Segmentation
Transformers
Safetensors
PyTorch
English
tren
feature-extraction
vision
image-feature-extraction
region-tokens
dinov3
custom_code
Instructions to use aryaaan12/T-REN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aryaaan12/T-REN with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="aryaaan12/T-REN", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("aryaaan12/T-REN", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
CHANGED
|
@@ -1,3 +1,17 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
# T-REN: Text-Aligned Region Encoder Network
|
| 2 |
|
| 3 |
**Authors**: [Savya Khosla](https://savya08.github.io/), [Sethuraman TV](https://github.com/sethuramanio), [Aryan Chadha](https://www.linkedin.com/in/aryan-chadha/), [Alex Schwing](https://www.alexander-schwing.de/), [Derek Hoiem](https://dhoiem.cs.illinois.edu/)
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
language:
|
| 4 |
+
- en
|
| 5 |
+
tags:
|
| 6 |
+
- vision
|
| 7 |
+
- image-segmentation
|
| 8 |
+
- image-feature-extraction
|
| 9 |
+
- region-tokens
|
| 10 |
+
- dinov3
|
| 11 |
+
- pytorch
|
| 12 |
+
library_name: transformers
|
| 13 |
+
---
|
| 14 |
+
|
| 15 |
# T-REN: Text-Aligned Region Encoder Network
|
| 16 |
|
| 17 |
**Authors**: [Savya Khosla](https://savya08.github.io/), [Sethuraman TV](https://github.com/sethuramanio), [Aryan Chadha](https://www.linkedin.com/in/aryan-chadha/), [Alex Schwing](https://www.alexander-schwing.de/), [Derek Hoiem](https://dhoiem.cs.illinois.edu/)
|