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README.md

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+---
+license: mit
+pipeline_tag: feature-extraction
+tags:
+- fmri
+- mindeye2
+- brain-decoding
+- multimodal
+- text-alignment
+---
+
+# TextAlign Model for MindEye2
+
+This repository contains the pre-trained weights and derived features for **[TextAlign-mindeye2](https://github.com/YKT-668/TextAlign-mindeye2)**.
+
+**GitHub Codebase:** [YKT-668/TextAlign-mindeye2](https://github.com/YKT-668/TextAlign-mindeye2)
+**Aligned Commit:** \`579ab6e1cb31f5e9e539fdccfef4c29984f5e870\`
+
+## Model Description
+TextAlign improves fMRI-to-image and fMRI-to-text retrieval by aligning brain representations with fine-grained text embeddings. It is built on top of MindEye2 (Scotti et al., 2024).
+
+- **Input:** fMRI betas (flattened cortical surface vertices).
+- **Output:** CLIP L/14 latent embeddings (Vision & Text aligned).
+
+## Directory Structure
+
+### `checkpoints/`
+- **`s1_textalign_stage1_FINAL_BEST_32/last.pth`** (25GB)
+  - The final Stage 1 model.
+  - Trained with counterfactual hard negatives.
+  - **Use this for inference.**
+- **`s1_textalign_stage0_repair_80G/last.pth`** (23GB)
+  - The intermediate Stage 0 model (pre-training).
+
+### `features/`
+Contains pre-computed text features required to run training or evaluation without access to the full NSD captions (which are restricted).
+- `train_coco_text_clip.pt`
+- `train_coco_captions.json`
+
+## Usage (Inference)
+
+Please refer to the [GitHub Repository](https://github.com/YKT-668/TextAlign-mindeye2) for installation.
+
+```bash
+# Example: Reconstruction Inference
+python src/recon_inference_run.py \
+    --subject 1 \
+    --ckpt_path checkpoints/s1_textalign_stage1_FINAL_BEST_32/last.pth \
+    --eval_only
+```
+
+## Licensing
+- Weights are released under MIT License.
+- Derived features (`features/`) respect the original NSD/COCO terms. Do not redistribute primitive data.

checkpoints/s1_textalign_stage1_FINAL_BEST_32/last.pth

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