HF Transformers Files removed

README.md

@@ -71,7 +71,7 @@ The weights of the Segformer (Original) model were used to get the inference res
 
 **Step 0.** Prerequisites
 
-- Pytorch: 2.3 (CUDA 12.1) (older versions should also work fine)
+- Pytorch: 2.0.1 (CUDA 12.1) (older versions should also work fine)
 
 **Step 1.** Clone Repository
 

segformer_plusplus/config.json

@@ -1,10 +0,0 @@
-{
-  "model_type": "segformerplusplus",
-  "architectures": ["SegFormerPlusPlus"],
-  "backbone": "b5",
-  "supported_backbones": ["b0", "b1", "b2", "b3", "b4", "b5"],
-  "head": "bsm_hq",
-  "supported_heads": ["bsm_hq", "bsm_fast", "n2d_2x2"],
-  "out_channels": 19,
-  "num_labels": 19
-}

segformer_plusplus/configuration_segformer_plusplus.py

@@ -1,10 +0,0 @@
-from transformers import PretrainedConfig
-
-class SegformerPlusPlusConfig(PretrainedConfig):
-    model_type = "segformer_plus_plus"
-
-    def __init__(self, backbone_cfg=None, decode_head_cfg=None, out_channels=19, **kwargs):
-        super().__init__(**kwargs)
-        self.backbone_cfg = backbone_cfg
-        self.decode_head_cfg = decode_head_cfg
-        self.out_channels = out_channels

segformer_plusplus/modeling_segformer_plusplus.py

@@ -1,13 +0,0 @@
-from transformers import PreTrainedModel
-from .configuration_segformer_plusplus import SegformerPlusPlusConfig
-from .build_model import SegFormer
-
-class SegformerPlusPlusModel(PreTrainedModel):
-    config_class = SegformerPlusPlusConfig
-
-    def __init__(self, config: SegformerPlusPlusConfig):
-        super().__init__(config)
-        self.model = SegFormer(config)
-
-    def forward(self, x, **kwargs):
-        return self.model(x)

segformer_plusplus/pytorch_model.bin

@@ -1,3 +0,0 @@
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-size 328287002