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
| { | |
| "architectures": [ | |
| "TRENModel" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_tren.TRENConfig", | |
| "AutoModel": "modeling_tren.TRENModel" | |
| }, | |
| "dtype": "float32", | |
| "hidden_dim": 1024, | |
| "image_resolution": 512, | |
| "merging_iou_threshold": 0.8, | |
| "merging_similarity_threshold": 0.975, | |
| "model_type": "tren", | |
| "num_attention_heads": 8, | |
| "num_decoder_layers": 2, | |
| "num_multiscale_regions": 3, | |
| "patch_size": 16, | |
| "text_embed_dim": 1024, | |
| "transformers_version": "5.2.0" | |
| } | |