Add paper checkpoints and PCA components

Include Geneformer, scVI, SSL and PCA with required loading files and original license notices.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot-Session: e1a3739a-1ad6-4a7d-9531-11fb3cc268f7

.gitignore

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+.DS_Store
+.cache/
+__pycache__/
+*.pyc
+.venv/
+validation-env/
+source-checkpoints/
+*-private-staging/
+private-*/
+private-*.json
+download-receipts.json
+model-validation*.json
+*.partial
+*.ckpt
+*.pt
+wandb/

CITATION.cff

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+cff-version: 1.2.0
+message: "Please cite the published Nature Methods paper when using this collection."
+title: "scFM-dataselection recovered checkpoint collection"
+type: dataset
+version: "pretraining-release"
+url: "https://huggingface.co/microsoft/scFM-dataselection"
+license: MIT
+authors:
+  - family-names: "DenAdel"
+    given-names: "Alan"
+  - family-names: "Hughes"
+    given-names: "Madeline"
+  - family-names: "Thoutam"
+    given-names: "Akshaya"
+  - family-names: "Gupta"
+    given-names: "Anay"
+  - family-names: "Navia"
+    given-names: "Andrew W."
+  - family-names: "Fusi"
+    given-names: "Nicolo"
+  - family-names: "Raghavan"
+    given-names: "Srivatsan"
+  - family-names: "Winter"
+    given-names: "Peter S."
+  - family-names: "Amini"
+    given-names: "Ava P."
+  - family-names: "Crawford"
+    given-names: "Lorin"
+preferred-citation:
+  type: article
+  authors:
+    - family-names: "DenAdel"
+      given-names: "Alan"
+    - family-names: "Hughes"
+      given-names: "Madeline"
+    - family-names: "Thoutam"
+      given-names: "Akshaya"
+    - family-names: "Gupta"
+      given-names: "Anay"
+    - family-names: "Navia"
+      given-names: "Andrew W."
+    - family-names: "Fusi"
+      given-names: "Nicolo"
+    - family-names: "Raghavan"
+      given-names: "Srivatsan"
+    - family-names: "Winter"
+      given-names: "Peter S."
+    - family-names: "Amini"
+      given-names: "Ava P."
+    - family-names: "Crawford"
+      given-names: "Lorin"
+  title: "Evaluating the role of pretraining dataset size and diversity on single-cell foundation model performance"
+  journal: "Nature Methods"
+  year: 2026
+  volume: "23"
+  issue: "7"
+  start: "1447"
+  end: "1457"
+  doi: "10.1038/s41592-026-03120-y"

LICENSE

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+    MIT License
+
+    Copyright (c) Microsoft Corporation.
+
+    Permission is hereby granted, free of charge, to any person obtaining a copy
+    of this software and associated documentation files (the "Software"), to deal
+    in the Software without restriction, including without limitation the rights
+    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+    copies of the Software, and to permit persons to whom the Software is
+    furnished to do so, subject to the following conditions:
+
+    The above copyright notice and this permission notice shall be included in all
+    copies or substantial portions of the Software.
+
+    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+    SOFTWARE

README.md

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+---
+license: mit
+tags:
+  - single-cell
+  - biology
+  - geneformer
+  - scvi
+  - self-supervised-learning
+  - pca
+  - safetensors
+inference: false
+---
+
+# scFM-dataselection pretraining checkpoints
+
+Model checkpoints and PCA components for **Evaluating the role of pretraining
+dataset size and diversity on single-cell foundation model performance**,
+DenAdel et al., *Nature Methods* (2026).
+
+- [Paper](https://doi.org/10.1038/s41592-026-03120-y)
+- [Code and preprocessing](https://github.com/microsoft/scFM-dataselection)
+
+## Models
+
+| Model | Count |
+|---|---:|
+| Geneformer | 125 |
+| scVI | 125 |
+| SSL/MLP | 125 |
+| PCA components | 80 |
+| **Total** | **455** |
+
+The full download is approximately **22.4 GB**: 375 neural network checkpoints
+and 80 PCA component matrices.
+
+Within `portable-checkpoints/`, models are grouped into `geneformer/`,
+`scvi/`, `ssl/` and `pca/`.
+
+The Geneformer, scVI and SSL models cover random sampling, cell-type
+reweighting and geometric sketching at 1, 10, 25, 50, 75 and 100 percent of
+the pretraining corpus. The collection also includes perturbation spike-in
+experiments. See `model-index.csv` for model folders and training settings.
+
+## Download
+
+Use Python **3.10**. The examples below were tested on CPU.
+
+```python
+from huggingface_hub import snapshot_download
+
+root = snapshot_download(
+    repo_id="microsoft/scFM-dataselection",
+    local_dir="scFM-dataselection",
+)
+```
+
+From the downloaded directory:
+
+```bash
+python -m pip install -r requirements.txt
+```
+
+To download individual models, use `allow_patterns` with the model folders
+listed in `model-index.csv`. Include `model-index.csv`, `tools/*`,
+`public-resources/*` and `requirements.txt` to use the loading code below.
+
+## Load a checkpoint
+
+Run these examples from the downloaded directory. They use small dummy inputs.
+
+```python
+import csv
+import sys
+import numpy as np
+import torch
+
+sys.path.insert(0, "tools")
+from portable_models import load_model
+
+with open("model-index.csv", newline="") as stream:
+    rows = list(csv.DictReader(stream))
+
+geneformer = load_model(
+    "portable-checkpoints/geneformer/random/idx_100pct_seed25"
+)
+with torch.no_grad():
+    logits = geneformer(input_ids=torch.tensor([[2, 3, 4, 5]])).logits
+
+ssl = load_model("portable-checkpoints/ssl/random/idx_100pct_seed25")
+with torch.no_grad():
+    latent, reconstruction = ssl(torch.ones(2, 19331))
+
+pca_row = next(row for row in rows if row["family"] == "PCA")
+components = load_model(pca_row["portable_directory"])
+projection = np.ones((2, 19331), dtype=components.dtype) @ components
+```
+
+For your own data, follow the paper's preprocessing. Geneformer requires
+ranked gene inputs and normalization using the tokenizer dictionaries in
+`public-resources/geneformer/`. SSL and PCA use the paper's 19,331-gene
+scTab order.
+
+For scVI, provide an AnnData object with raw counts in `X` and `var_names`
+matching the `gene_names` order in the model's `config.json`.
+
+```python
+scvi_model = load_model(
+    "portable-checkpoints/scvi/random/idx_100pct_seed25",
+    adata=your_anndata,
+)
+latent = scvi_model.get_latent_representation()
+```
+
+## License
+
+The model weights, PCA components and loading code are licensed under
+**MIT**. Geneformer tokenizer files use **Apache-2.0**, and the included SSL
+code uses MIT. See `LICENSE` and `THIRD_PARTY_NOTICES.md` for the full terms
+and copyright notices.
+
+## Citation
+
+Please cite the paper when using these checkpoints:
+
+> DenAdel, A., Hughes, M., Thoutam, A., et al. Evaluating the role of pretraining
+> dataset size and diversity on single-cell foundation model performance.
+> Nature Methods 23, 1447-1457 (2026).
+> https://doi.org/10.1038/s41592-026-03120-y
+
+Questions about the checkpoints can be raised in the
+[paper's code repository](https://github.com/microsoft/scFM-dataselection/issues).

THIRD_PARTY_NOTICES.md

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+# Third-party notices
+
+The study weights, PCA components and loading code use the MIT license in
+`LICENSE`, with the Microsoft copyright notice. Third-party files retain
+the licenses and copyright notices listed below.
+
+## Paper code and gene order
+
+- Project: https://github.com/microsoft/scFM-dataselection
+- Included gene-order file: `public-resources/sctab/adata_var.csv`.
+- License: MIT, Copyright (c) Microsoft Corporation.
+- Full notice: `licenses/scFM-dataselection-MIT.txt`.
+
+## SSL implementation
+
+- Project: https://github.com/v-mahughes/ssl_in_scg
+- Included source files: `public-resources/ssl-source/base.py` and
+  `public-resources/ssl-source/cellnet_autoencoder.py`.
+- Authors credited by the project: Till Richter, Mojtaba Bahrami, Yufan Xia
+  and Felix Fischer.
+- License: MIT, Copyright (c) 2024 Till Richter.
+- Full notice: `licenses/ssl_in_scg-MIT.txt`.
+
+The loading adapters in `tools/` use these source files to construct the models.
+
+## Geneformer tokenizer files
+
+- Source: https://github.com/lcrawlab/Geneformer
+- Original project: https://huggingface.co/ctheodoris/Geneformer
+- Original work: Christine V. Theodoris and collaborators.
+- Included dictionaries: `token_dictionary.pkl`, `gene_median_dictionary.pkl`
+  and `gene_name_id_dict.pkl` in `public-resources/geneformer/`.
+- License: Apache-2.0.
+- Full terms: `licenses/Geneformer-Apache-2.0.txt`.
+
+The Geneformer weights are models trained for this study, not upstream
+Geneformer pretrained weights.
+
+## Dependencies and data
+
+Runtime packages are installed separately and retain their own licenses.
+The scTab corpus is not included. See https://github.com/theislab/scTab for
+dataset access and terms, and the paper code for preprocessing.

licenses/Geneformer-Apache-2.0.txt

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licenses/scFM-dataselection-MIT.txt

@@ -0,0 +1,21 @@
+    MIT License
+
+    Copyright (c) Microsoft Corporation.
+
+    Permission is hereby granted, free of charge, to any person obtaining a copy
+    of this software and associated documentation files (the "Software"), to deal
+    in the Software without restriction, including without limitation the rights
+    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+    copies of the Software, and to permit persons to whom the Software is
+    furnished to do so, subject to the following conditions:
+
+    The above copyright notice and this permission notice shall be included in all
+    copies or substantial portions of the Software.
+
+    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+    SOFTWARE

licenses/ssl_in_scg-MIT.txt

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2024 Till Richter
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

model-index.csv

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+family,sampling,percentage,seed,experiment_type,portable_directory,checkpoint_role
+Geneformer,celltype_reweighted,1,0,main,portable-checkpoints/geneformer/celltype_reweighted/idx_1pct_seed0,primary_export
+Geneformer,celltype_reweighted,1,1,main,portable-checkpoints/geneformer/celltype_reweighted/idx_1pct_seed1,primary_export
+Geneformer,celltype_reweighted,1,2,main,portable-checkpoints/geneformer/celltype_reweighted/idx_1pct_seed2,primary_export
+Geneformer,celltype_reweighted,1,3,main,portable-checkpoints/geneformer/celltype_reweighted/idx_1pct_seed3,primary_export
+Geneformer,celltype_reweighted,1,4,main,portable-checkpoints/geneformer/celltype_reweighted/idx_1pct_seed4,primary_export
+Geneformer,celltype_reweighted,10,5,main,portable-checkpoints/geneformer/celltype_reweighted/idx_10pct_seed5,primary_export
+Geneformer,celltype_reweighted,10,6,main,portable-checkpoints/geneformer/celltype_reweighted/idx_10pct_seed6,primary_export
+Geneformer,celltype_reweighted,10,7,main,portable-checkpoints/geneformer/celltype_reweighted/idx_10pct_seed7,primary_export
+Geneformer,celltype_reweighted,10,8,main,portable-checkpoints/geneformer/celltype_reweighted/idx_10pct_seed8,primary_export
+Geneformer,celltype_reweighted,10,9,main,portable-checkpoints/geneformer/celltype_reweighted/idx_10pct_seed9,primary_export
+Geneformer,celltype_reweighted,25,10,main,portable-checkpoints/geneformer/celltype_reweighted/idx_25pct_seed10,primary_export
+Geneformer,celltype_reweighted,25,11,main,portable-checkpoints/geneformer/celltype_reweighted/idx_25pct_seed11,primary_export
+Geneformer,celltype_reweighted,25,12,main,portable-checkpoints/geneformer/celltype_reweighted/idx_25pct_seed12,primary_export
+Geneformer,celltype_reweighted,25,13,main,portable-checkpoints/geneformer/celltype_reweighted/idx_25pct_seed13,primary_export
+Geneformer,celltype_reweighted,25,14,main,portable-checkpoints/geneformer/celltype_reweighted/idx_25pct_seed14,primary_export
+Geneformer,celltype_reweighted,50,15,main,portable-checkpoints/geneformer/celltype_reweighted/idx_50pct_seed15,primary_export
+Geneformer,celltype_reweighted,50,16,main,portable-checkpoints/geneformer/celltype_reweighted/idx_50pct_seed16,primary_export
+Geneformer,celltype_reweighted,50,17,main,portable-checkpoints/geneformer/celltype_reweighted/idx_50pct_seed17,primary_export
+Geneformer,celltype_reweighted,50,18,main,portable-checkpoints/geneformer/celltype_reweighted/idx_50pct_seed18,primary_export
+Geneformer,celltype_reweighted,50,19,main,portable-checkpoints/geneformer/celltype_reweighted/idx_50pct_seed19,primary_export
+Geneformer,celltype_reweighted,75,20,main,portable-checkpoints/geneformer/celltype_reweighted/idx_75pct_seed20,primary_export
+Geneformer,celltype_reweighted,75,21,main,portable-checkpoints/geneformer/celltype_reweighted/idx_75pct_seed21,primary_export
+Geneformer,celltype_reweighted,75,22,main,portable-checkpoints/geneformer/celltype_reweighted/idx_75pct_seed22,primary_export
+Geneformer,celltype_reweighted,75,23,main,portable-checkpoints/geneformer/celltype_reweighted/idx_75pct_seed23,primary_export
+Geneformer,celltype_reweighted,75,24,main,portable-checkpoints/geneformer/celltype_reweighted/idx_75pct_seed24,primary_export
+Geneformer,geometric_sketching,1,0,main,portable-checkpoints/geneformer/geometric_sketching/idx_1pct_seed0,primary_export
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