Model: brain-bzh/reve-large
Author: brain-bzh
Pipeline: feature-extraction
Library: transformers
Tags: transformers, safetensors, reve, feature-extraction, eeg, neuroscience, foundation-model, pytorch, custom_code, arxiv:2510.21585, license:other, model-index, region:us
Card metadata: library_name: transformers
tags: eeg, neuroscience, foundation-model, pytorch
license: other
extra_gated_prompt: ## EEG FOUNDATION MODEL RESPONSIBLE USE AGREEMENT
This model is available for general use (research, commercial, and personal), provided strictly that you adhere to the following privacy and safety standards. By requesting access, you agree to be bound by the following ethical principles and the regulatory guidance outlined in **EDPB Opinion 28/2024**.
1. **No Privacy Intrusion or Reconstruction** You acknowledge that AI models trained on personal data may not be fully anonymous and can be vulnerable to attacks. You expressly agree **NOT** to:
  - Attempt to extract, infer, or reconstruct subject-level EEG data or personal information from the model weights or outputs.
  - Perform "Model Inversion" or "Membership Inference" attacks to extract statistical data related to specific individuals.
  - Attempt to re-identify individuals from the model's embeddings.

2. **No Harm, Surveillance, or Discrimination** In line with protecting fundamental rights, you will not use this model for:
  - **Biometric Identification:** Continuous monitoring, behavioral profiling, or identification of natural persons.
  - **Discrimination:** Any purpose that leads to unfair treatment of individuals or groups, or exploits vulnerabilities (e.g., age, disability).
  - **Manipulation:** Coercing or exploiting users, particularly vulnerable populations, or infringing on human autonomy.
  
3. **Fair Use, Security, and Data Minimisation** If you deploy this model, you accept accountability for the processing. You must:
  - **Minimize Data:** Ensure any additional data used with the model is limited, pseudonymised where possible, and securely handled.
  - **Be Transparent:** Any research or deployment must clearly state the purpose, limitations, and safeguards implemented to protect rights.
  - **Secure the Deployment:** Implement measures to prevent unauthorized access or adversarial attacks on the model.

4. **Redistribution and Access Revocation**
  - **No Redistribution:** You will not share, host, or distribute the model weights or derivatives to users without permission; they must access the model via this repository to agree to these terms.
  - **Dataset Withdrawal:** If any underlying dataset becomes closed or restricted, access to this model may be revoked or replaced by a retrained version.
extra_gated_fields: Full Name: text
Organization / Entity: text
I want to use this model for: type: select
options: Research, Industry, Education, label: Other
value: other
geo: ip_location
I agree to the non-identification, no-harm, and privacy terms above: checkbox
I acknowledge that access may be revoked if underlying datasets are restricted: checkbox
extra_gated_description: Access is open to verified users who agree to strict privacy, no-harm, and non-identification policies compliant with EDPB guidelines.
extra_gated_button_content: Accept Terms & Request Access
model-index: name: Reve-large Evaluation Results
results: task: type: feature-extraction
dataset: name: Mumtaz-LP
type: Mumtaz-LP
metrics: type: Accuracy
value: 0.985
name: Accuracy
verified: no, task: type: feature-extraction
dataset: name: MAT-LP
type: MAT-LP
metrics: type: Accuracy
value: 0.712
name: Accuracy
verified: no, task: type: feature-extraction
dataset: name: TUAB-LP
type: TUAB-LP
metrics: type: Accuracy
value: 0.821
name: Accuracy
verified: no, task: type: feature-extraction
dataset: name: PhysionetMIT-LP
type: PhysionetMIT-LP
metrics: type: Accuracy
value: 0.617
name: Accuracy
verified: no, task: type: feature-extraction
dataset: name: BCIC-IV-2a-LP
type: BCIC-IV-2a-LP
metrics: type: Accuracy
value: 0.603
name: Accuracy
verified: no, task: type: feature-extraction
dataset: name: ISRUC-LP
type: ISRUC-LP
metrics: type: Accuracy
value: 0.758
name: Accuracy
verified: no, task: type: feature-extraction
dataset: name: HMC-LP
type: HMC-LP
metrics: type: Accuracy
value: 0.71
name: Accuracy
verified: no, task: type: feature-extraction
dataset: name: BCIC2020-3A-LP
type: BCIC2020-3A-LP
metrics: type: Accuracy
value: 0.39
name: Accuracy
verified: no, task: type: feature-extraction
dataset: name: TUEV-LP
type: TUEV-LP
metrics: type: Accuracy
value: 0.63
name: Accuracy
verified: no, task: type: feature-extraction
dataset: name: FACED-LP
type: FACED-LP
metrics: type: Accuracy
value: 0.469
name: Accuracy
verified: no
Likes: 6 | All-time downloads: 613
Created: 2025-11-28 13:44:55