Instructions to use knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF", dtype="auto")

llama-cpp-python

How to use knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF",
	filename="Magnum-v4-Cydonia-v1.2-22B-F16.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF: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 knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF: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 knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF with Ollama:
```
ollama run hf.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF:Q4_K_M
```

Unsloth Studio

How to use knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF 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 knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF 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 knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF to start chatting

How to use knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF with Docker Model Runner:
```
docker model run hf.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF:Q4_K_M
```

Lemonade

How to use knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Magnum-v4-Cydonia-v1.2-22B-GGUF-Q4_K_M

List all available models

lemonade list

Magnum-v4-Cydonia-v1.2-22B-GGUF

File size: 3,797 Bytes

86d4ce8

---
base_model:
- knifeayumu/Magnum-v4-Cydonia-v1.2-22B
language:
- en
license: other
license_name: mrl
license_link: https://mistral.ai/licenses/MRL-0.1.md
library_name: transformers
---

## Llamacpp Quantizations of knifeayumu/Magnum-v4-Cydonia-v1.2-22B

Using [llama.cpp](https://github.com/ggerganov/llama.cpp/) release [b3985](https://github.com/ggerganov/llama.cpp/releases/tag/b3985) for quantization.

Original model: [knifeayumu/Magnum-v4-Cydonia-v1.2-22B](https://huggingface.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B)

## Quant Types:

| Filename | Quant type | File Size |
| -------- | ---------- | --------- |
| [Magnum-v4-Cydonia-v1.2-22B-F16.gguf](https://huggingface.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF/blob/main/Magnum-v4-Cydonia-v1.2-22B-F16.gguf) | F16 | 44.5 GB |
| [Magnum-v4-Cydonia-v1.2-22B-Q8_0.gguf](https://huggingface.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF/blob/main/Magnum-v4-Cydonia-v1.2-22B-Q8_0.gguf) | Q8_0 | 23.6 GB |
| [Magnum-v4-Cydonia-v1.2-22B-Q6_K.gguf](https://huggingface.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF/blob/main/Magnum-v4-Cydonia-v1.2-22B-Q6_K.gguf) | Q6_K | 18.3 GB |
| [Magnum-v4-Cydonia-v1.2-22B-Q5_K_M.gguf](https://huggingface.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF/blob/main/Magnum-v4-Cydonia-v1.2-22B-Q5_K_M.gguf) | Q5_K_M | 15.7 GB |
| [Magnum-v4-Cydonia-v1.2-22B-Q5_K_S.gguf](https://huggingface.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF/blob/main/Magnum-v4-Cydonia-v1.2-22B-Q5_K_S.gguf) | Q5_K_S | 15.3 GB |
| [Magnum-v4-Cydonia-v1.2-22B-Q4_K_M.gguf](https://huggingface.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF/blob/main/Magnum-v4-Cydonia-v1.2-22B-Q4_K_M.gguf) | Q4_K_M | 13.3 GB |
| [Magnum-v4-Cydonia-v1.2-22B-Q4_K_S.gguf](https://huggingface.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF/blob/main/Magnum-v4-Cydonia-v1.2-22B-Q4_K_S.gguf) | Q4_K_S | 12.7 GB |
| [Magnum-v4-Cydonia-v1.2-22B-Q3_K_L.gguf](https://huggingface.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF/blob/main/Magnum-v4-Cydonia-v1.2-22B-Q3_K_L.gguf) | Q3_K_L | 11.7 GB |
| [Magnum-v4-Cydonia-v1.2-22B-Q3_K_M.gguf](https://huggingface.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF/blob/main/Magnum-v4-Cydonia-v1.2-22B-Q3_K_M.gguf) | Q3_K_M | 10.8 GB |
| [Magnum-v4-Cydonia-v1.2-22B-Q3_K_S.gguf](https://huggingface.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF/blob/main/Magnum-v4-Cydonia-v1.2-22B-Q3_K_S.gguf) | Q3_K_S | 9.64 GB |
| [Magnum-v4-Cydonia-v1.2-22B-Q2_K.gguf](https://huggingface.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B-GGUF/blob/main/Magnum-v4-Cydonia-v1.2-22B-Q2_K.gguf) | Q2_K | 8.27 GB |


![Too Horny](https://huggingface.co/knifeayumu/Magnum-v4-Cydonia-v1.2-22B/resolve/main/Magnum-v4-Cydonia-v1.2-22B.png)

# Magnum? More like Deagle (dies in cringe)

[Cydonia-v1.2-Magnum-v4-22B](https://huggingface.co/knifeayumu/Cydonia-v1.2-Magnum-v4-22B) but inverse... Some prefer [anthracite-org/magnum-v4-22b](https://huggingface.co/anthracite-org/magnum-v4-22b) over [TheDrummer/Cydonia-22B-v1.2](https://huggingface.co/TheDrummer/Cydonia-22B-v1.2) so this merge is born.

This is a merge of pre-trained language models created using [mergekit](https://github.com/arcee-ai/mergekit).

## Merge Details
### Merge Method

This model was merged using the SLERP merge method.

### Models Merged

The following models were included in the merge:
* [TheDrummer/Cydonia-22B-v1.2](https://huggingface.co/TheDrummer/Cydonia-22B-v1.2)
* [anthracite-org/magnum-v4-22b](https://huggingface.co/anthracite-org/magnum-v4-22b)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: anthracite-org/magnum-v4-22b
  - model: TheDrummer/Cydonia-22B-v1.2
merge_method: slerp
base_model: anthracite-org/magnum-v4-22b
parameters:
  t: [0.1, 0.3, 0.6, 0.3, 0.1]
dtype: bfloat16
```