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
- llama.cpp
How to use CodexCon-OS/Amethyst-Core with llama.cpp:
Install from brew
brew install llama.cpp # 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
Install from WinGet (Windows)
winget install llama.cpp # 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
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 new
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
- 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
File size: 1,255 Bytes
c5466c7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | XLPHY Amethyst Core License Notice
This repository distributes quantized GGUF model artifacts derived from the
Google Gemma family for Project: XLPHY AI. These models are released under
dual licensing depending on the base model.
Model Artifact Terms
### Gemma 3 Models (Amethyst Arc 1B)
Amethyst Arc models derived from Gemma 3 are subject to the Gemma Terms of Use.
You may use, copy, modify, distribute, and deploy these artifacts only as
permitted by those terms.
**Official Terms:** https://ai.google.dev/gemma/terms
**Upstream Reference:** https://huggingface.co/google/gemma-3-1b-it
### Gemma 4 Models (Amethyst Beam E2B)
Amethyst Beam models derived from Gemma 4 are released under the Apache License 2.0.
You may use, copy, modify, distribute, and deploy these artifacts in accordance
with the terms of the Apache License 2.0.
**Official Terms:** https://www.apache.org/licenses/LICENSE-2.0
**Upstream Reference:** https://huggingface.co/google/gemma-4-e2b-it
No Additional Rights
Except where explicitly stated above, this repository does not grant rights
beyond the respective licenses for each model artifact.
Attribution
Google, Gemma, and related marks are trademarks of Google LLC.
No endorsement by Google DeepMind is implied.
|