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Improve model card: Add pipeline tag, project page link, and link to paper

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This PR improves the model card by:

- Adding the `image-classification` pipeline tag, making the model discoverable in the Hugging Face model search.
- Adding a link to the project page for more comprehensive documentation.
- Linking the model to the original paper.
- Correcting the `library_name` to `timm`.

Files changed (1) hide show
  1. README.md +11 -7
README.md CHANGED
@@ -1,13 +1,14 @@
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-
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  ---
 
 
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  tags:
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  - image-classification
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  - ecology
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  - fungi
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  - FGVC
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- library_name: FungiTastic Dataset
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- license: cc-by-nc-4.0
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  ---
 
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  # Model card for BVRA/swin_base_patch4_window7_224.in1k_ft_fungitastic-mini_224
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  ## Model Details
@@ -16,8 +17,8 @@ license: cc-by-nc-4.0
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  - Params (M): 87.0
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  - Image size: 224 x 224
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  - **Papers:**
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- - **Original:** --> ???
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- - **Train Dataset:** FungiTastic --> https://arxiv.org/pdf/2408.13632
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  ## Model Usage
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  ### Image Embeddings
@@ -25,7 +26,7 @@ license: cc-by-nc-4.0
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  import timm
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  import torch
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  import torchvision.transforms as T
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- from PIL import Image
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  from urllib.request import urlopen
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  model = timm.create_model("hf-hub:BVRA/swin_base_patch4_window7_224.in1k_ft_fungitastic-mini_224", pretrained=True)
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  model = model.eval()
@@ -37,6 +38,9 @@ output = model(train_transforms(img).unsqueeze(0))
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  # output is a (1, num_features) shaped tensor
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  ```
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  ## Citation
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  ```bibtex
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  @article{picek2024fungitastic,
@@ -67,4 +71,4 @@ output = model(train_transforms(img).unsqueeze(0))
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  year={2022},
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  publisher={Multidisciplinary Digital Publishing Institute}
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  }
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- ```
 
 
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  ---
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+ library_name: timm
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+ license: cc-by-nc-4.0
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  tags:
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  - image-classification
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  - ecology
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  - fungi
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  - FGVC
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+ pipeline_tag: image-classification
 
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  ---
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+
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  # Model card for BVRA/swin_base_patch4_window7_224.in1k_ft_fungitastic-mini_224
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  ## Model Details
 
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  - Params (M): 87.0
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  - Image size: 224 x 224
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  - **Papers:**
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+ - **Original:** [FungiTastic: A multi-modal dataset and benchmark for image categorization](https://huggingface.co/papers/2408.13632)
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+ - **Train Dataset:** FungiTastic
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  ## Model Usage
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  ### Image Embeddings
 
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  import timm
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  import torch
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  import torchvision.transforms as T
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+ from PIL Image
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  from urllib.request import urlopen
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  model = timm.create_model("hf-hub:BVRA/swin_base_patch4_window7_224.in1k_ft_fungitastic-mini_224", pretrained=True)
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  model = model.eval()
 
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  # output is a (1, num_features) shaped tensor
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  ```
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+ ## Project Page
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+ For more details about the FungiTastic dataset and benchmark, please refer to the project page: [https://bohemianvra.github.io/FungiTastic/](https://bohemianvra.github.io/FungiTastic/)
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+
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  ## Citation
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  ```bibtex
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  @article{picek2024fungitastic,
 
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  year={2022},
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  publisher={Multidisciplinary Digital Publishing Institute}
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  }
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+ ```