Instructions to use jruffle/tabpfn_transcriptome_32d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TabPFN
How to use jruffle/tabpfn_transcriptome_32d with TabPFN:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| tags: | |
| - transcriptomics | |
| - dimensionality-reduction | |
| - tabpfn | |
| - TRACERx | |
| license: mit | |
| # TabPFN Model - transcriptome mode - 32D | |
| Pre-trained TabPFN embedding model with UMAP reduction. | |
| ## Details | |
| - **Mode**: transcriptome-centric compression | |
| - **Dimensions**: 32 | |
| - **Training data**: TRACERx lung cancer transcriptomics | |
| - **Created**: 2026-01-13T17:09:42.158983 | |
| - **Reduction method**: UMAP (non-linear) | |
| ## Usage | |
| ```python | |
| import joblib | |
| from huggingface_hub import snapshot_download | |
| local_dir = snapshot_download("jruffle/tabpfn_transcriptome_32d") | |
| model = joblib.load(f"{local_dir}/model.joblib") | |
| ``` | |