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
File size: 495 Bytes
485629f 98795ce 485629f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | {
"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"
}
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