Remap weights to refactored transformers SwinBackbone layout (nobg 0.2.0); weights unchanged

README.md

@@ -31,5 +31,19 @@ from nobg import BiRefNet
 model = BiRefNet.from_pretrained("nobg/BiRefNet-Finetuned")
 ```
 
+
+## Citation
+If you use this model, please cite the original paper
+(https://arxiv.org/abs/2401.03407):
+```bibtex
+@article{zheng2024birefnet,
+  title={Bilateral Reference for High-Resolution Dichotomous Image Segmentation},
+  author={Zheng, Peng and Gao, Dehong and Fan, Deng-Ping and Liu, Li and
+          Laaksonen, Jorma and Ouyang, Wanli and Sebe, Nicu},
+  journal={CAAI Artificial Intelligence Research},
+  year={2024}
+}
+```
+
 ## Contributions
 Any contributions are welcome at https://github.com/feyninc/nobg

config.json

@@ -10,12 +10,14 @@
   "embed_dim": 192,
   "image_size": 1024,
   "mlp_ratio": 4.0,
+  "nobg_version": "0.2.0",
   "num_heads": [
     6,
     12,
     24,
     48
   ],
+  "num_layers": 4,
   "patch_size": 4,
   "use_gradient_attention": true,
   "use_image_patch_injection": true,

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f4fd0c3815cea82af6239e0bfd419830259227c777e8cbdf08a0ad6d14653256
-size 884878824
+oid sha256:ea77387d72ce19029a3fb808a6d05b86fe05d849c066c68b68fe97b3773cf74e
+size 880926192