Upload README.md with huggingface_hub

README.md

@@ -1,3 +1,16 @@
+---
+license: gemma
+base_model: google/gemma-2b-it
+tags:
+  - quantized
+  - int4
+  - mobile
+  - tflite
+  - gemma
+library_name: mediapipe
+---
+
+
 # Gemma AI Models
 
 This directory contains the downloaded Gemma 3N (2B parameters) model files required for the M.AI application's on-device AI features.
@@ -14,34 +27,3 @@ This directory contains the downloaded Gemma 3N (2B parameters) model files requ
     *   **Source:** Google's Gemma 2B repository (Hugging Face).
     *   **SHA-256:** `61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2`
 
-## 🚀 Next Steps: Hosting & Configuration
-
-Since these models are gated by Google, you **cannot** use direct Hugging Face links in your production app. You must self-host them.
-
-### 1. Upload to Hosting Service
-Upload both files to a public file host. Recommended options:
-*   **GitHub Releases:** Create a release in your repo (e.g., `v1.0-models`) and attach these files. (Free, fast, public).
-*   **Firebase Storage:** Upload to your project's storage bucket.
-*   **AWS S3 / Cloudflare R2:** Standard object storage.
-
-### 2. Get Public URLs
-Obtain the direct download link for each file.
-*   *Test:* Running `curl -I <LINK>` should return `200 OK` and the correct file size (not a login page).
-
-### 3. Update App Configuration
-Open `apps/ai_apps/maiv2/lib/core/config/environment_config.dart` and update the `production` configuration:
-
-```dart
-static const EnvironmentConfig production = EnvironmentConfig(
-  // ... other config ...
-  gemmaModelUrl: 'https://your-host.com/path/to/gemma-1.1-2b-it-gpu-int4.bin',
-  gemmaTokenizerUrl: 'https://your-host.com/path/to/tokenizer.spm',
-  
-  // Use the SHA-256 checksums listed above
-  gemmaModelChecksum: '53f7defdb5554dd517a6863d2d605a144d14361d6c486bbeaac2870497b75747',
-  gemmaTokenizerChecksum: '61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2',
-);
-```
-
-### 4. Verify
-Run the app in release mode. The "Download AI Model" button in the chat interface will now fetch these specific files and verify their integrity using the checksums.