Text Generation
GGUF
English
Gemma 3
quantized
vision
edge-ai
local-first
xlphy
codexcon
1b
4b
12b
27b
imatrix
conversational
Instructions to use CodexCon-OS/Amethyst-Core with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use CodexCon-OS/Amethyst-Core with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="CodexCon-OS/Amethyst-Core", filename="amethyst-arc-1b-Q4_K_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use CodexCon-OS/Amethyst-Core with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf CodexCon-OS/Amethyst-Core:Q4_K_M # Run inference directly in the terminal: llama cli -hf CodexCon-OS/Amethyst-Core:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf CodexCon-OS/Amethyst-Core:Q4_K_M # Run inference directly in the terminal: llama cli -hf CodexCon-OS/Amethyst-Core:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf CodexCon-OS/Amethyst-Core:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf CodexCon-OS/Amethyst-Core:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf CodexCon-OS/Amethyst-Core:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf CodexCon-OS/Amethyst-Core:Q4_K_M
Use Docker
docker model run hf.co/CodexCon-OS/Amethyst-Core:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use CodexCon-OS/Amethyst-Core with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CodexCon-OS/Amethyst-Core" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CodexCon-OS/Amethyst-Core", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/CodexCon-OS/Amethyst-Core:Q4_K_M
- Ollama
How to use CodexCon-OS/Amethyst-Core with Ollama:
ollama run hf.co/CodexCon-OS/Amethyst-Core:Q4_K_M
- Unsloth Studio
How to use CodexCon-OS/Amethyst-Core with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for CodexCon-OS/Amethyst-Core to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for CodexCon-OS/Amethyst-Core to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for CodexCon-OS/Amethyst-Core to start chatting
- Atomic Chat new
- Docker Model Runner
How to use CodexCon-OS/Amethyst-Core with Docker Model Runner:
docker model run hf.co/CodexCon-OS/Amethyst-Core:Q4_K_M
- Lemonade
How to use CodexCon-OS/Amethyst-Core with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull CodexCon-OS/Amethyst-Core:Q4_K_M
Run and chat with the model
lemonade run user.Amethyst-Core-Q4_K_M
List all available models
lemonade list
Upload 3 files
Browse files
LICENSE
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XLPHY Amethyst Core License Notice
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This repository distributes quantized GGUF model artifacts derived from the
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Google Gemma family for Project: XLPHY AI. These models are released under
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dual licensing depending on the base model.
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Model Artifact Terms
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### Gemma 3 Models (Amethyst Arc 1B)
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Amethyst Arc models derived from Gemma 3 are subject to the Gemma Terms of Use.
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You may use, copy, modify, distribute, and deploy these artifacts only as
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permitted by those terms.
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**Official Terms:** https://ai.google.dev/gemma/terms
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**Upstream Reference:** https://huggingface.co/google/gemma-3-1b-it
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### Gemma 4 Models (Amethyst Beam E2B)
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Amethyst Beam models derived from Gemma 4 are released under the Apache License 2.0.
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You may use, copy, modify, distribute, and deploy these artifacts in accordance
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with the terms of the Apache License 2.0.
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**Official Terms:** https://www.apache.org/licenses/LICENSE-2.0
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**Upstream Reference:** https://huggingface.co/google/gemma-4-e2b-it
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No Additional Rights
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Except where explicitly stated above, this repository does not grant rights
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beyond the respective licenses for each model artifact.
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Attribution
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Google, Gemma, and related marks are trademarks of Google LLC.
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No endorsement by Google DeepMind is implied.
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NOTICE
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XLPHY Amethyst Core Model Distribution Notice
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This distribution package contains rebranded and quantized GGUF model files:
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Gemma 3 Models (Amethyst Arc):
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- amethyst-arc-1b-Q4_K_M.gguf
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- amethyst-arc-1b-Q5_K_M.gguf
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- amethyst-arc-1b-Q6_K.gguf
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Gemma 4 Models (Amethyst Beam):
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- amethyst-beam-e2b-Q4_K_M.gguf
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- amethyst-beam-e2b-Q5_K_M.gguf
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- amethyst-beam-e2b-Q6_K.gguf
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These files are derivative/packaged artifacts based on upstream Gemma models:
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- google/gemma-3-1b-it (Licensed under Gemma Terms of Use)
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- google/gemma-4-e2b-it (Licensed under Apache License 2.0)
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Upstream model provider: Google DeepMind.
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Dual Licensing
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This package distributes models under dual licensing:
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- Gemma 3 derivatives are redistributed under Gemma Terms of Use
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- Gemma 4 derivatives are redistributed under Apache License 2.0
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See the LICENSE file in this directory for detailed license information:
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https://ai.google.dev/gemma/terms (Gemma Terms)
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https://www.apache.org/licenses/LICENSE-2.0 (Apache License 2.0)
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Attribution and notices are provided here for transparency and compliance.
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This NOTICE file does not modify applicable license terms.
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No endorsement by the upstream provider is implied.
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README.md
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---
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license:
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---
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license:
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- gemma
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- apache-2.0
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language:
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- en
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base_model:
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- google/gemma-3-1b-it
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- google/gemma-4-e2b-it
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tags:
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- Gemma 3
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- gguf
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- quantized
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- vision
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- text-generation
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- edge-ai
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- local-first
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- xlphy
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- codexcon
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- 1b
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- 4b
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- 12b
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- 27b
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---
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# 🔮 XLPHY Amethyst (Gemma Series) for Project: XLPHY AI
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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.
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> **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.
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## 🧠 Model Selection
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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.
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| File Name (Template) | Tier Identity | Base Engine | Primary Purpose | License | Available Quants |
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| --- | --- | --- | --- | --- | --- |
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| `amethyst-arc-1b-[quant].gguf` | arc | Gemma 3 1B IT | Ultra-fast local execution and IoT. | Gemma | `Q4_K_M`, `Q5_K_M`, `Q6_K` |
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| `amethyst-beam-e2b-[quant].gguf` | Core | Gemma 4 E2B IT | Main driver with Vision support. | Apache 2.0 | `Q4_K_M`, `Q5_K_M`, `Q6_K` |
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## 📦 Quantization Guide
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- **Q4_K_M (Low):** Fastest and most memory-efficient. Ideal for mobile and entry-level hardware.
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- **Q5_K_M (Medium):** The "sweet spot" for Amethyst, with minimal quality differences from the original model.
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- **Q6_K (High):** Near-lossless performance for users who prioritize maximum accuracy.
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## 🛠️ Implementation & Runtime
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Designed for the Project: XLPHY AI "Offline-First" philosophy. Best executed via:
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- **XLPHY Desktop App** (Native Integration)
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- **`llama.cpp` / `llama-cli`**
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- Any GGUF-compatible inference engine supporting Gemma 3 and Gemma 4
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## 🔐 Checksums (SHA256)
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To ensure file integrity during the XLPHY automated download process:
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| Tier | Q4_K_M | Q5_K_M | Q6_K |
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| --- | --- | --- | --- |
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| Arc (1B) | `12bf0fff8815d5f73a3c9b586bd8fee8e7b248c935de70dec367679873d0f29d` | `59a10a3c8dc8a9c0bda2c8882198073b1cfebbb2b443aa2fc4cfca4f92eeb805` | `ccad0cb14e9008f699f4b820110b899cf81983a987c40a05a8a1128d2fb713fb` |
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| Beam (E2B) | `cded614c9b24be92e5a868d2ba38fb24e15dfea34fc650193c475a6debc233a7` | `43b6d9cfc1108e172b9ff99759ce7c2052bbed5dd7c4b4675ca63a04b6ed8dfc` | `b4c977371027c423ba6e36c7ca6e31e11803853224046f62d94a24a827e4f041` |
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## ⚖️ Attribution & Licensing
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These files are redistributed/repackaged quantized derivatives of the Google Gemma family.
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- **Original Architecture:** Developed by Google DeepMind
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- **Optimization:** Repackaged by CodexCon Digital Solutions for Project: XLPHY AI
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- **Amethyst Arc (Gemma 3):** Gemma Terms of Use
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- **Amethyst Beam (Gemma 4):** Apache License 2.0
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## ⚠️ Limitations & Safety
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- **Hallucinations:** Like all LLMs, these models may produce incorrect information.
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- **Human-in-the-loop:** Always validate technical outputs, especially for vision-based tasks or critical code.
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- **Non-Critical Use:** Not intended for medical, legal, or other high-stakes safety-critical applications.
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---
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Developed by **CodexCon** | Lead Founder: **Cid Cruz**
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