File size: 3,325 Bytes
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license:
- gemma
- apache-2.0
language:
- en
base_model:
- google/gemma-3-1b-it
- google/gemma-4-e2b-it
tags:
- Gemma 3
- gguf
- quantized
- vision
- text-generation
- edge-ai
- local-first
- xlphy
- codexcon
- 1b
- 4b
- 12b
- 27b
---
# 🔮 XLPHY Amethyst (Gemma Series) for Project: XLPHY AI
XLPHY Amethyst is a suite of high-efficiency, local-first AI models optimized specifically for the Project: XLPHY AI ecosystem. These models are repackaged and quantized to provide a premium, low-latency, and multimodal experience for autonomous agents and sovereign AI applications.
> **Developer Note:** These are optimized derivatives of the Google Gemma 3 series, rebranded and tuned for seamless integration within the Project: XLPHY AI autonomous agent architecture.
## 🧠 Model Selection
The Amethyst series is built for Project: XLPHY AI and is divided into four "Gemstone Tiers." Each tier is available in `Q4_K_M`, `Q5_K_M`, and `Q6_K` quantization levels.
| File Name (Template) | Tier Identity | Base Engine | Primary Purpose | License | Available Quants |
| --- | --- | --- | --- | --- | --- |
| `amethyst-arc-1b-[quant].gguf` | arc | Gemma 3 1B IT | Ultra-fast local execution and IoT. | Gemma | `Q4_K_M` |
| `amethyst-beam-e2b-[quant].gguf` | Core | Gemma 4 E2B IT | Main driver with Vision support. | Apache 2.0 | `Q4_K_M`, `Q6_K`, `Q8_0` |
## 📦 Quantization Guide
- **Q4_K_M (Low):** Fastest and most memory-efficient. Ideal for mobile and entry-level hardware.
- **Q5_K_M (Medium):** The "sweet spot" for Amethyst, with minimal quality differences from the original model.
- **Q6_K (High):** Near-lossless performance for users who prioritize maximum accuracy.
## 🛠️ Implementation & Runtime
Designed for the Project: XLPHY AI "Offline-First" philosophy. Best executed via:
- **XLPHY Desktop App** (Native Integration)
- **`llama.cpp` / `llama-cli`**
- Any GGUF-compatible inference engine supporting Gemma 3 and Gemma 4
## 🔐 Checksums (SHA256)
To ensure file integrity during the XLPHY automated download process:
| Tier | Q4_K_M | Q6_K | Q8_0 | mmproj |
| --- | --- | --- | --- | --- |
| Arc (1B) | `12bf0fff8815d5f73a3c9b586bd8fee8e7b248c935de70dec367679873d0f29d` | `X` | `X` | `X` |
| Beam (E2B) | `6c950d754366dd8b372fd17a40497ba5f130a46d833b4c5bccc9f6bb6382ce1e` | `5a352f63b59e1b37bac5071e3aed65e8954883a1625bf6676bf9aa2381295beb` | `6febf73c7c6b44c550ba857ceca3788262ce2272603ca16b1f2609556205dea3` | `b23366bec60eda708aa54816c8f72dfdfedd5c5ccbe4e7db500aa7724bd14b20` |
## ⚖️ Attribution & Licensing
These files are redistributed/repackaged quantized derivatives of the Google Gemma family.
- **Original Architecture:** Developed by Google DeepMind
- **Optimization:** Repackaged by CodexCon Digital Solutions for Project: XLPHY AI
- **Amethyst Arc (Gemma 3):** Gemma Terms of Use
- **Amethyst Beam (Gemma 4):** Apache License 2.0
## ⚠️ Limitations & Safety
- **Hallucinations:** Like all LLMs, these models may produce incorrect information.
- **Human-in-the-loop:** Always validate technical outputs, especially for vision-based tasks or critical code.
- **Non-Critical Use:** Not intended for medical, legal, or other high-stakes safety-critical applications.
---
Developed by **CodexCon** | Lead Founder: **Cid Cruz**
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