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README.md
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---
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## Model Details
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- **Developed by:**
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- **Funded by
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- **Language(s) (NLP):** {{ language | default("[More Information Needed]", true)}}
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- **License:** {{ license | default("[More Information Needed]", true)}}
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- **Finetuned from model [optional]:** {{ finetuned_from | default("[More Information Needed]", true)}}
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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{{ direct_use | default("[More Information Needed]", true)}}
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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{{ downstream_use | default("[More Information Needed]", true)}}
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###
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{{ out_of_scope_use | default("[More Information Needed]", true)}}
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## Technical Specifications
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## Model Details
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Phikon is a self-supervised learning model for histopathology.
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To learn more about how to use the model, we encourage you to read our blog post and view this Colab notebook.
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### Model Description
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- **Developed by:** Owkin
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- **Funded by:** Owkin and CNRS
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- **Model type:** Vision Transformer
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## Uses
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### Direct Use
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The primary use of the Phikon model can be used for feature extraction from histology image tiles.
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### Downstream Use
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The model can be used for cancer classification on a variety of cancer subtypes. The model can also be finetuned to specialise on cancer subtypes.
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## Technical Specifications
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