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Update README.md

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@@ -52,6 +52,15 @@ Visit our GitHub repo: [https://github.com/ZhengPeng7/BiRefNet](https://github.c
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  ### 1. Load BiRefNet:
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  #### Use codes from GitHub + weights from HuggingFace
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  > Only use the weights on HuggingFace -- Pro: codes are always latest; Con: Need to clone the BiRefNet repo from my GitHub.
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@@ -64,16 +73,19 @@ cd BiRefNet
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  ```python
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  # Load weights
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  from models.birefnet import BiRefNet
 
 
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  birefnet = BiRefNet.from_pretrained('zhengpeng7/birefnet')
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- ```
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- #### Use codes + weights from HuggingFace
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- > Only use the weights on HuggingFace -- Pro: No need to download BiRefNet codes manually; Con: Codes on HuggingFace might not be latest version (I'll try to keep them always latest).
 
 
 
 
 
 
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- ```python
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- # Load BiRefNet with weights
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- from transformers import AutoModelForImageSegmentation
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- birefnet = AutoModelForImageSegmentation.from_pretrained('zhengpeng7/birefnet', trust_remote_code=True)
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  ```
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  #### Use the loaded BiRefNet for inference
 
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  ### 1. Load BiRefNet:
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+ #### Use codes + weights from HuggingFace
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+ > Only use the weights on HuggingFace -- Pro: No need to download BiRefNet codes manually; Con: Codes on HuggingFace might not be latest version (I'll try to keep them always latest).
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+
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+ ```python
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+ # Load BiRefNet with weights
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+ from transformers import AutoModelForImageSegmentation
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+ birefnet = AutoModelForImageSegmentation.from_pretrained('zhengpeng7/birefnet', trust_remote_code=True)
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+ ```
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+
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  #### Use codes from GitHub + weights from HuggingFace
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  > Only use the weights on HuggingFace -- Pro: codes are always latest; Con: Need to clone the BiRefNet repo from my GitHub.
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  ```python
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  # Load weights
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  from models.birefnet import BiRefNet
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+
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+ # Option-1: From Hugging Face Models
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  birefnet = BiRefNet.from_pretrained('zhengpeng7/birefnet')
 
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+ # Option-2: From local disk
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+ import torch
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+ from utils import check_state_dict
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+
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+ birefnet = BiRefNet(bb_pretrained=False)
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+ state_dict = torch.load(PATH_TO_WEIGHT, map_location='cpu')
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+ state_dict = check_state_dict(state_dict)
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+ birefnet.load_state_dict(state_dict)
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  ```
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  #### Use the loaded BiRefNet for inference