Instructions to use QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF", dtype="auto")

llama-cpp-python

How to use QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF",
	filename="HomerCreativeAnvita-Mix-Qw7B.Q2_K.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/HomerCreativeAnvita-Mix-Qw7B-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 QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf QuantFactory/HomerCreativeAnvita-Mix-Qw7B-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 QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/HomerCreativeAnvita-Mix-Qw7B-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 QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF:Q4_K_M
```

Unsloth Studio new

How to use QuantFactory/HomerCreativeAnvita-Mix-Qw7B-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 QuantFactory/HomerCreativeAnvita-Mix-Qw7B-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 QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF to start chatting

Pi new

How to use QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf QuantFactory/HomerCreativeAnvita-Mix-Qw7B-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": "QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use QuantFactory/HomerCreativeAnvita-Mix-Qw7B-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 QuantFactory/HomerCreativeAnvita-Mix-Qw7B-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 QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.HomerCreativeAnvita-Mix-Qw7B-GGUF-Q4_K_M

List all available models

lemonade list

QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF

This is quantized version of suayptalha/HomerCreativeAnvita-Mix-Qw7B created using llama.cpp

Original Model Card

Merged Model

This is a merge of pre-trained language models created using mergekit.

This model is currently ranked #1 on the Open LLM Leaderboard among models up to 13B parameters!

Merge Details

Merge Method

This model was merged using the SLERP merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

base_model: ZeroXClem/Qwen2.5-7B-HomerCreative-Mix
dtype: bfloat16
merge_method: slerp
parameters:
  t:
  - filter: self_attn
    value: [0.0, 0.5, 0.3, 0.7, 1.0]
  - filter: mlp
    value: [1.0, 0.5, 0.7, 0.3, 0.0]
  - value: 0.5
slices:
- sources:
  - layer_range: [0, 28]
    model: ZeroXClem/Qwen2.5-7B-HomerCreative-Mix
  - layer_range: [0, 28]
    model: ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	34.62
IFEval (0-Shot)	78.08
BBH (3-Shot)	36.98
MATH Lvl 5 (4-Shot)	31.04
GPQA (0-shot)	8.61
MuSR (0-shot)	14.73
MMLU-PRO (5-shot)	38.28

Downloads last month: 60

GGUF

Model size

8B params

Architecture

qwen2

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

Inference Providers NEW

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

Model tree for QuantFactory/HomerCreativeAnvita-Mix-Qw7B-GGUF

ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix

ZeroXClem/Qwen2.5-7B-HomerCreative-Mix

Merge model

this model

Evaluation results

strict accuracy on IFEval (0-Shot)
Open LLM Leaderboard

78.080
normalized accuracy on BBH (3-Shot)
Open LLM Leaderboard

36.980
exact match on MATH Lvl 5 (4-Shot)
Open LLM Leaderboard

31.040
acc_norm on GPQA (0-shot)
Open LLM Leaderboard

8.610
acc_norm on MuSR (0-shot)
Open LLM Leaderboard

14.730
accuracy on MMLU-PRO (5-shot)
test set Open LLM Leaderboard

38.280