mgbam
/

OpenCLIP-BiomedCLIP-Finetuned

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mgbam commited on Mar 7

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d51e9f2

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1 Parent(s): b53ba4b

Update README.md

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README.md +3 -3

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@@ -18,10 +18,10 @@ from PIL import Image
 # 1) Load the fine-tuned model
 model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms(
-    "hf-hub:your-username/OpenCLIP-BiomedCLIP-Finetuned",
     pretrained=None
 )
-tokenizer = open_clip.get_tokenizer("hf-hub:your-username/OpenCLIP-BiomedCLIP-Finetuned")
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model.to(device)
@@ -68,7 +68,7 @@ import open_clip
 from PIL import Image
 model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms(
-    "hf-hub:your-username/OpenCLIP-BiomedCLIP-Finetuned",
     pretrained=None
 )
 tokenizer = open_clip.get_tokenizer("hf-hub:your-username/OpenCLIP-BiomedCLIP-Finetuned")

 # 1) Load the fine-tuned model
 model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms(
+    "hf-hub:mgbam/OpenCLIP-BiomedCLIP-Finetuned",
     pretrained=None
 )
+tokenizer = open_clip.get_tokenizer("hf-hub:mgbam/OpenCLIP-BiomedCLIP-Finetuned")
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model.to(device)
 from PIL import Image
 model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms(
+    "hf-hub:mgbam/OpenCLIP-BiomedCLIP-Finetuned",
     pretrained=None
 )
 tokenizer = open_clip.get_tokenizer("hf-hub:your-username/OpenCLIP-BiomedCLIP-Finetuned")