Instructions to use matth/flowformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use matth/flowformer with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("matth/flowformer", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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@@ -29,6 +29,8 @@ The pretrained model is trained with the the markers: *TIME, FSC-A, FSC-W, SSC-A
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output = flowformer(x, markers=["Marker1", "Marker2", "Marker3"])
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```
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## Citation
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If you use this project please consider citing our work
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output = flowformer(x, markers=["Marker1", "Marker2", "Marker3"])
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```
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For more information about model usage as well as hands-on examples check out this demo notebook from my colleague Florian Kowarsch: [https://github.com/CaRniFeXeR/python4FCM_Examples/blob/main/hyperflow2023.ipynb](https://github.com/CaRniFeXeR/python4FCM_Examples/blob/main/hyperflow2023.ipynb)
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## Citation
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If you use this project please consider citing our work
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