Instructions to use jsfs11/WONMSeverusDevil-TIES-7B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jsfs11/WONMSeverusDevil-TIES-7B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="jsfs11/WONMSeverusDevil-TIES-7B-GGUF",
	filename="wonmseverusdevil-ties-7b.Q6_K.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use jsfs11/WONMSeverusDevil-TIES-7B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf jsfs11/WONMSeverusDevil-TIES-7B-GGUF:Q6_K
# Run inference directly in the terminal:
llama-cli -hf jsfs11/WONMSeverusDevil-TIES-7B-GGUF:Q6_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf jsfs11/WONMSeverusDevil-TIES-7B-GGUF:Q6_K
# Run inference directly in the terminal:
llama-cli -hf jsfs11/WONMSeverusDevil-TIES-7B-GGUF:Q6_K

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 jsfs11/WONMSeverusDevil-TIES-7B-GGUF:Q6_K
# Run inference directly in the terminal:
./llama-cli -hf jsfs11/WONMSeverusDevil-TIES-7B-GGUF:Q6_K

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 jsfs11/WONMSeverusDevil-TIES-7B-GGUF:Q6_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf jsfs11/WONMSeverusDevil-TIES-7B-GGUF:Q6_K

Use Docker

docker model run hf.co/jsfs11/WONMSeverusDevil-TIES-7B-GGUF:Q6_K

LM Studio
Jan
Ollama
How to use jsfs11/WONMSeverusDevil-TIES-7B-GGUF with Ollama:
```
ollama run hf.co/jsfs11/WONMSeverusDevil-TIES-7B-GGUF:Q6_K
```

Unsloth Studio new

How to use jsfs11/WONMSeverusDevil-TIES-7B-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 jsfs11/WONMSeverusDevil-TIES-7B-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 jsfs11/WONMSeverusDevil-TIES-7B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for jsfs11/WONMSeverusDevil-TIES-7B-GGUF to start chatting

Docker Model Runner
How to use jsfs11/WONMSeverusDevil-TIES-7B-GGUF with Docker Model Runner:
```
docker model run hf.co/jsfs11/WONMSeverusDevil-TIES-7B-GGUF:Q6_K
```

Lemonade

How to use jsfs11/WONMSeverusDevil-TIES-7B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull jsfs11/WONMSeverusDevil-TIES-7B-GGUF:Q6_K

Run and chat with the model

lemonade run user.WONMSeverusDevil-TIES-7B-GGUF-Q6_K

List all available models

lemonade list

WONMSeverusDevil-TIES-7B

WONMSeverusDevil-TIES-7B is a merge of the following models using LazyMergekit:

# Open-LLM Benchmark Results:
 WONMSeverusDevil-TIES-7B LLM AutoEval📑
|       Model            |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
|------------------------|------:|------:|---------:|-------:|------:|
|WONMSeverusDevil-TIES-7B|  45.26|  77.07|     72.47|   48.85|  60.91|

🧩 Configuration

models:
  - model: FelixChao/WestSeverus-7B-DPO-v2
    parameters:
      density: [1, 0.7, 0.1] # density gradient
      weight: 1.0
  - model: jsfs11/WestOrcaNeuralMarco-DPO-v2-DARETIES-7B
    parameters:
      density: 0.65
      weight: [0, 0.3, 0.7, 1] # weight gradient
  - model: mlabonne/Daredevil-7B
    parameters:
      density: 0.33
      weight:
        - filter: mlp
          value: 0.5
        - value: 0
merge_method: ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  normalize: true
  int8_mask: true
dtype: float16

Downloads last month: 11

GGUF

Model size

7B params

Architecture

llama

Hardware compatibility

6-bit

8-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for jsfs11/WONMSeverusDevil-TIES-7B-GGUF

PetroGPT/WestSeverus-7B-DPO-v2

jsfs11/WestOrcaNeuralMarco-DPO-v2-DARETIES-7B

mlabonne/Daredevil-7B

Merge model

this model