Instructions to use NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF 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 NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF:IQ2_XS
# Run inference directly in the terminal:
llama cli -hf NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF:IQ2_XS

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF:IQ2_XS
# Run inference directly in the terminal:
llama cli -hf NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF:IQ2_XS

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 NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF:IQ2_XS
# Run inference directly in the terminal:
./llama-cli -hf NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF:IQ2_XS

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 NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF:IQ2_XS
# Run inference directly in the terminal:
./build/bin/llama-cli -hf NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF:IQ2_XS

Use Docker

docker model run hf.co/NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF:IQ2_XS

LM Studio
Jan
Ollama
How to use NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF with Ollama:
```
ollama run hf.co/NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF:IQ2_XS
```
Unsloth Desktop
Docker Model Runner
How to use NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF with Docker Model Runner:
```
docker model run hf.co/NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF:IQ2_XS
```

Lemonade

How to use NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull NexesQuants/alchemonaut_QuartetAnemoi-70B-iMat.GGUF:IQ2_XS

Run and chat with the model

lemonade run user.alchemonaut_QuartetAnemoi-70B-iMat.GGUF-IQ2_XS

List all available models

lemonade list

Atomic Chat

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Check out the documentation for more information.

GGUF quants for : https://huggingface.co/alchemonaut/QuartetAnemoi-70B-t0.0001

Available : Q3_K_M, IQ3_XXS. Otw : IQ2_XS

I recommand you folks to try this model, because it's quite an efficient merge of Miqu, WinterGoddess, AuroraNights, and XWin.

The Theta Rope 1,000,000 of Miqu, hence the 32k context, is functional up to 16k accordingly to my tests, and probably above (I need a smaller quant to test, which is otw).

To use it with a quantized KV cache for a higher context, here's KoboldCPP Frankenstein version with several different KV cache quantization lebels to chose from : https://github.com/Nexesenex/kobold.cpp/releases

Downloads last month: 376

GGUF

Model size

69B params

Architecture

llama

Hardware compatibility

1-bit

2-bit

3-bit

4-bit

View +2 variants

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