Marraffini-Giovanni/fbert-1m
feature-extraction model by Marraffini-Giovanni
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
F-BERT is a small Transformer encoder for parcellated fMRI timeseries, pretrained on about 4,000 hours of resting-state and task fMRI from 162 openly available datasets. It is trained by kernel alignment to the flattened connectome: the pairwise similarities between the embeddings of short recording windows are aligned with the pairwise similarities between the recordings' functional-connectivity matrices after a spectral filter, FC^alpha = V diag(lambda^alpha) V^T with alpha = 0.35, which recalibrates the eigenvalues of each subject's connectome. The encoder reads a window of a scan and produces one embedding per recording that can be used with a frozen linear probe for cognition, sex, age, diagnosis and subject identification. This is the 1M-parameter model. The 8M model is at Marraffini-Giovanni/fbert-8m. The code, the transform and every table of the paper are at github.com/GioMarraffini/fc-power. band-passed to 0.01–0.08 Hz and z-scored per region, shape (batch, 450, time). Positional encoding is sinusoidal, so a…
Read the full model card ↗ · Preview checked 2026-09-25T08:17:39.796Z
Inside the original model card — Document outline
- Model Card for F-BERT-1M
- Model Details
- Uses
- Inference
- Intermediate checkpoints
- Evaluation
- Training
- Data
- Hyperparameters
- Bias, Risks, and Limitations
- Citation
- Model Card Contact
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
Links from the model card
References supplied by the publisher, not independently verified endorsements. Check the destination before downloading files or entering credentials.
Documentation belongs to its respective authors. Reported project/model license: cc-by-nc-4.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
Marraffini-Giovanni/fbert-1m is a feature-extraction model repository published by Marraffini-Giovanni on Hugging Face. The source reports the pytorch library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- feature-extraction
- Library
- pytorch
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- cc-by-nc-4.0
- Access
- Not gated by Hugging Face
- Created
- 2026-09-25T06:03:53.000Z
- Last modified
- 2026-09-25T06:09:34.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.
Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-25T06:37:40.528Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.