Add comprehensive OLLAMA_README for Ollama users

- Step-by-step setup guide with Modelfile requirement
- Explains bilingual behavior configuration
- Recommended settings for Raspberry Pi
- Complete examples and use cases

OLLAMA_README.md

@@ -0,0 +1,197 @@
+# Gemma3 Smart Q4 — Bilingual Offline AI for Raspberry Pi
+
+**Quantized Gemma 3 1B optimized for edge devices. Fully offline, bilingual (Italian/English), privacy-first.**
+
+---
+
+## 🚀 Quick Start
+
+**IMPORTANT**: To enable bilingual behavior, you must create a Modelfile with the bilingual SYSTEM prompt.
+
+### Step 1: Pull the base model
+
+```bash
+# Pull Q4_0 (recommended - faster, smaller)
+ollama pull antconsales/antonio-gemma3-smart-q4
+
+# Or pull Q4_K_M variant (better quality for long conversations)
+ollama pull antconsales/antonio-gemma3-smart-q4:q4_k_m
+```
+
+### Step 2: Create Modelfile with bilingual configuration
+
+```bash
+cat > Modelfile <<'EOF'
+FROM antconsales/antonio-gemma3-smart-q4
+
+PARAMETER temperature 0.7
+PARAMETER top_p 0.9
+PARAMETER num_ctx 1024
+PARAMETER num_thread 4
+PARAMETER num_batch 32
+PARAMETER repeat_penalty 1.05
+PARAMETER stop "<end_of_turn>"
+PARAMETER stop "</s>"
+
+SYSTEM """You are an offline AI assistant running on a Raspberry Pi. You MUST detect the user's language and respond in the SAME language:
+
+- If the user writes in Italian, respond ONLY in Italian
+- If the user writes in English, respond ONLY in English
+
+Sei un assistente AI offline su Raspberry Pi. DEVI rilevare la lingua dell'utente e rispondere nella STESSA lingua:
+
+- Se l'utente scrive in italiano, rispondi SOLO in italiano
+- Se l'utente scrive in inglese, rispondi SOLO in inglese
+
+Always match the user's language choice."""
+EOF
+```
+
+### Step 3: Create the configured model
+
+```bash
+ollama create gemma3-bilingual -f Modelfile
+```
+
+### Step 4: Run it!
+
+```bash
+ollama run gemma3-bilingual
+
+# Test in Italian
+>>> ciao! come va?
+
+# Test in English
+>>> hello! how are you?
+```
+
+**Why this is needed**: The base model is instruction-tuned but doesn't automatically switch languages. The SYSTEM prompt explicitly tells it to match the user's language.
+
+## ✨ Features
+
+- 🔒 **100% Offline** — No cloud, no tracking, no internet required
+- 🗣️ **Bilingual** — Automatically detects and responds in Italian or English
+- ⚡ **Fast** — 3.67 tokens/s on Raspberry Pi 4 (Q4_0)
+- 🎯 **Optimized** — Tuned parameters for Pi 4/5 hardware
+- 🔐 **Privacy-First** — All inference on-device
+
+## 📊 Benchmarks (Raspberry Pi 4, 4GB RAM)
+
+| Model | Speed | Size | Use Case |
+|-------|-------|------|----------|
+| **Q4_0** ⭐ | **3.67 t/s** | 720 MB | Default choice (faster, smaller) |
+| **Q4_K_M** | 3.56 t/s | 806 MB | Better coherence in long conversations |
+
+**Tested on**: Raspberry Pi OS (Debian Bookworm), Ollama runtime
+
+## 💬 Example Interactions
+
+Once you've created the model with the Modelfile (see Quick Start above):
+
+### Italian
+```bash
+ollama run gemma3-bilingual "Ciao! Spiegami cos'è un sensore di prossimità."
+```
+
+### English
+```bash
+ollama run gemma3-bilingual "What is a Raspberry Pi and what can I do with it?"
+```
+
+### Code-switching (IT/EN mixed)
+```bash
+ollama run gemma3-bilingual "Explain GPIO in English, poi dimmi come usarlo in italiano"
+```
+
+The model automatically detects the language and responds appropriately **when using the Modelfile configuration**!
+
+## 🎯 Use Cases
+
+- **Privacy-first personal assistants** — All inference on-device
+- **Offline home automation** — Control IoT without cloud dependencies
+- **Voice assistants** — Fast enough for real-time speech (3.67 t/s)
+- **Educational Pi projects** — Learn AI/ML on affordable hardware
+- **Bilingual chatbots** — IT/EN customer support, documentation
+- **Embedded systems** — Industrial applications requiring offline inference
+
+## ⚙️ Recommended Settings (Raspberry Pi 4/5)
+
+For **optimal performance**, use these parameters in your Modelfile:
+
+```dockerfile
+FROM antconsales/antonio-gemma3-smart-q4
+
+PARAMETER num_ctx 1024       # Context length (512 for faster response, 1024 for longer conversations)
+PARAMETER num_thread 4        # Utilize all 4 cores on Raspberry Pi 4
+PARAMETER num_batch 32        # Optimized for throughput on Pi
+PARAMETER temperature 0.7     # Balanced creativity vs consistency
+PARAMETER top_p 0.9           # Nucleus sampling for diverse responses
+PARAMETER repeat_penalty 1.05 # Reduces repetitive outputs
+PARAMETER stop "<end_of_turn>"
+PARAMETER stop "</s>"
+
+SYSTEM """
+You are an offline AI assistant running on a Raspberry Pi. Automatically detect the user's language (Italian or English) and respond in the same language. Be concise, practical, and helpful.
+
+Sei un assistente AI offline che opera su Raspberry Pi. Rileva automaticamente la lingua dell'utente (italiano o inglese) e rispondi nella stessa lingua. Sii conciso, pratico e utile.
+"""
+```
+
+**For voice assistants** or **real-time chat**, reduce `num_ctx` to `512` for faster responses.
+
+## 🛠️ Technical Details
+
+- **Base Model**: [Google Gemma 3 1B IT](https://huggingface.co/google/gemma-3-1b-it)
+- **Quantization**: Q4_0 and Q4_K_M (llama.cpp)
+- **Context Length**: 1024 tokens (configurable down to 512)
+- **Vocabulary Size**: 262,144 tokens
+- **Architecture**: Gemma3ForCausalLM
+- **Supported Platforms**: Raspberry Pi 4/5, Mac M1/M2, Linux ARM64, x86-64
+
+## 🔒 Model Verification
+
+Verify downloaded models using SHA256 checksums:
+
+| File | SHA256 Checksum |
+|------|----------------|
+| `gemma3-1b-q4_0.gguf` | `d1d037446a2836db7666aa6ced3ce460b0f7f2ba61c816494a098bb816f2ad55` |
+| `gemma3-1b-q4_k_m.gguf` | `c02d2e6f68fd34e9e66dff6a31d3f95fccb6db51f2be0b51f26136a85f7ec1f0` |
+
+```bash
+# Verify checksum (on Linux/Mac with Ollama)
+# Models are stored in ~/.ollama/models/blobs/
+sha256sum ~/.ollama/models/blobs/sha256-*
+```
+
+## 🔗 Links
+
+- **Ollama**: https://ollama.com/antconsales/antonio-gemma3-smart-q4
+- **HuggingFace**: https://huggingface.co/chill123/antonio-gemma3-smart-q4
+- **GitHub** (demos, benchmarks, code): https://github.com/antconsales/gemma3-smart-q4
+
+## 📜 License
+
+This model is a **derivative work** of [Google's Gemma 3 1B](https://huggingface.co/google/gemma-3-1b-it).
+
+**License**: Gemma License
+Please review and comply with the [Gemma License Terms](https://ai.google.dev/gemma/terms) before using this model.
+
+**Quantization, optimization, and bilingual configuration** by Antonio ([antconsales](https://github.com/antconsales)).
+
+For licensing questions regarding the base model, refer to Google's official Gemma documentation.
+
+---
+
+## 📝 Version History
+
+### v0.1.0 (2025-10-21)
+- Initial release
+- Two quantizations: Q4_0 (720 MB) and Q4_K_M (806 MB)
+- Bilingual IT/EN support with automatic language detection
+- Optimized for Raspberry Pi 4 (3.56-3.67 tokens/s)
+- Tested on Raspberry Pi OS (Debian Bookworm) with Ollama
+
+---
+
+**Built with ❤️ for privacy and edge computing**
+*Empowering offline AI, one Raspberry Pi at a time.* 🇮🇹