Feature Extraction
Transformers
Safetensors
jolia
medical
radiology
ct
3d
vision
foundation-model
self-supervised
custom_code
Instructions to use raidium/Jolia with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raidium/Jolia with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="raidium/Jolia", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("raidium/Jolia", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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<!--
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license: SET BEFORE PUBLISHING. cc-by-nc-4.0 is a placeholder commonly used for
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research medical models — confirm Raidium's choice (and any data-use terms from
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year = {2026},
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howpublished = {\url{https://huggingface.co/raidium/Jolia}}
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}
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```
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---
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license: other
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tags:
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- medical
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---
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<!--
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license: SET BEFORE PUBLISHING. cc-by-nc-4.0 is a placeholder commonly used for
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research medical models — confirm Raidium's choice (and any data-use terms from
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year = {2026},
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howpublished = {\url{https://huggingface.co/raidium/Jolia}}
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}
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```
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