Instructions to use ND911/Franken-Mistral-Merlinite-Maid-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ND911/Franken-Mistral-Merlinite-Maid-gguf with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ND911/Franken-Mistral-Merlinite-Maid-gguf", dtype="auto")

llama-cpp-python

How to use ND911/Franken-Mistral-Merlinite-Maid-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="ND911/Franken-Mistral-Merlinite-Maid-gguf",
	filename="Franken-Mistral-Merlinite-Maid.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use ND911/Franken-Mistral-Merlinite-Maid-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 ND911/Franken-Mistral-Merlinite-Maid-gguf
# Run inference directly in the terminal:
llama cli -hf ND911/Franken-Mistral-Merlinite-Maid-gguf

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ND911/Franken-Mistral-Merlinite-Maid-gguf
# Run inference directly in the terminal:
llama cli -hf ND911/Franken-Mistral-Merlinite-Maid-gguf

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 ND911/Franken-Mistral-Merlinite-Maid-gguf
# Run inference directly in the terminal:
./llama-cli -hf ND911/Franken-Mistral-Merlinite-Maid-gguf

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 ND911/Franken-Mistral-Merlinite-Maid-gguf
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ND911/Franken-Mistral-Merlinite-Maid-gguf

Use Docker

docker model run hf.co/ND911/Franken-Mistral-Merlinite-Maid-gguf

LM Studio
Jan
Ollama
How to use ND911/Franken-Mistral-Merlinite-Maid-gguf with Ollama:
```
ollama run hf.co/ND911/Franken-Mistral-Merlinite-Maid-gguf
```

Unsloth Studio

How to use ND911/Franken-Mistral-Merlinite-Maid-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 ND911/Franken-Mistral-Merlinite-Maid-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 ND911/Franken-Mistral-Merlinite-Maid-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ND911/Franken-Mistral-Merlinite-Maid-gguf to start chatting

Atomic Chat new
Docker Model Runner
How to use ND911/Franken-Mistral-Merlinite-Maid-gguf with Docker Model Runner:
```
docker model run hf.co/ND911/Franken-Mistral-Merlinite-Maid-gguf
```

Lemonade

How to use ND911/Franken-Mistral-Merlinite-Maid-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ND911/Franken-Mistral-Merlinite-Maid-gguf

Run and chat with the model

lemonade run user.Franken-Mistral-Merlinite-Maid-gguf-{{QUANT_TAG}}

List all available models

lemonade list

Franken-Mistral-Merlinite-Maid 7B gguf q8_0

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

Merge Details

see below

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:

slices:
  - sources:
      - model: ND911/Franken-Merlinite-Maid
        layer_range: [0, 32]
      - model: l3utterfly/mistral-7b-v0.1-layla-v4-chatml
        layer_range: [0, 32]
merge_method: slerp
base_model: ND911/Franken-Merlinite-Maid
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

Downloads last month: 1

GGUF

Model size

7B params

Architecture

llama

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

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ND911/Franken-Merlinite-Maid

l3utterfly/mistral-7b-v0.1-layla-v4-chatml

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