Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+---
+# TA-SAE Model Card
+
+This repository contains the trained Temporal-Aware Sparse AutoEncoder (TA-SAE) models for different layers.
+
+## Model Description
+
+TA-SAE is a specialized autoencoder model designed for temporal feature extraction and compression. Each layer model represents a different level of feature abstraction in the network.
+
+
+## Usage
+
+### Installation
+
+```python
+pip install huggingface_hub
+```
+
+### Loading Models
+
+#### Download a specific file:
+
+```python
+from huggingface_hub import hf_hub_download
+
+# Download specific layer model
+file_path = hf_hub_download(
+    repo_id="jeix/TA-SAE",
+    filename="PixArt/SAE-Layer0/model.safetensors"
+)
+```
+
+#### Download all files for a specific layer:
+
+```python
+from huggingface_hub import snapshot_download
+
+# Download all files for layer0
+local_dir = snapshot_download(
+    repo_id="jeix/TA-SAE",
+    repo_type="model",
+    allow_patterns="PixArt/SAE-Layer0/*"
+)
+```
+
+#### Download all layers:
+
+```python
+local_dir = snapshot_download(
+    repo_id="jeix/TA-SAE",
+    repo_type="model",
+    allow_patterns="PixArt/SAE-Layer*/*"
+)
+```
+
+### Using Command Line
+
+#### Install CLI tool
+
+```bash
+pip install -U huggingface_hub
+```
+
+#### Download specific file
+
+```bash
+huggingface-cli download jeix/TA-SAE --local-dir ./download --include "PixArt/SAE-Layer0/model.safetensors"
+```
+
+## Model Files Description
+
+Each layer directory contains the following files:
+
+- `model.safetensors`: The main model weights
+- `optimizer.bin`: Optimizer state
+- `scheduler.bin`: Learning rate scheduler state
+- `random_states_0.pkl`: Random state information
+- `scaler.pt`: Data scaling parameters
+
+<!-- ## License
+
+[Add your license information here]
+
+## Citation
+
+[Add citation information if applicable]
+
+## Contact
+
+[Add your contact information or github profile] -->