Instructions to use Quant-Cartel/Questionable-MN-12B-iMat-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Quant-Cartel/Questionable-MN-12B-iMat-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Quant-Cartel/Questionable-MN-12B-iMat-GGUF", dtype="auto")

llama-cpp-python

How to use Quant-Cartel/Questionable-MN-12B-iMat-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Quant-Cartel/Questionable-MN-12B-iMat-GGUF",
	filename="Questionable-MN-12B-iMat-IQ3_M.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 Quant-Cartel/Questionable-MN-12B-iMat-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Quant-Cartel/Questionable-MN-12B-iMat-GGUF:IQ3_M
# Run inference directly in the terminal:
llama-cli -hf Quant-Cartel/Questionable-MN-12B-iMat-GGUF:IQ3_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Quant-Cartel/Questionable-MN-12B-iMat-GGUF:IQ3_M
# Run inference directly in the terminal:
llama-cli -hf Quant-Cartel/Questionable-MN-12B-iMat-GGUF:IQ3_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 Quant-Cartel/Questionable-MN-12B-iMat-GGUF:IQ3_M
# Run inference directly in the terminal:
./llama-cli -hf Quant-Cartel/Questionable-MN-12B-iMat-GGUF:IQ3_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 Quant-Cartel/Questionable-MN-12B-iMat-GGUF:IQ3_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Quant-Cartel/Questionable-MN-12B-iMat-GGUF:IQ3_M

Use Docker

docker model run hf.co/Quant-Cartel/Questionable-MN-12B-iMat-GGUF:IQ3_M

LM Studio
Jan
Ollama
How to use Quant-Cartel/Questionable-MN-12B-iMat-GGUF with Ollama:
```
ollama run hf.co/Quant-Cartel/Questionable-MN-12B-iMat-GGUF:IQ3_M
```

Unsloth Studio new

How to use Quant-Cartel/Questionable-MN-12B-iMat-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 Quant-Cartel/Questionable-MN-12B-iMat-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 Quant-Cartel/Questionable-MN-12B-iMat-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Quant-Cartel/Questionable-MN-12B-iMat-GGUF to start chatting

Docker Model Runner
How to use Quant-Cartel/Questionable-MN-12B-iMat-GGUF with Docker Model Runner:
```
docker model run hf.co/Quant-Cartel/Questionable-MN-12B-iMat-GGUF:IQ3_M
```

Lemonade

How to use Quant-Cartel/Questionable-MN-12B-iMat-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Quant-Cartel/Questionable-MN-12B-iMat-GGUF:IQ3_M

Run and chat with the model

lemonade run user.Questionable-MN-12B-iMat-GGUF-IQ3_M

List all available models

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PROUDLY PRESENTS

Mistral-Large-Instruct-2411-iMat-GGUF

Quantized from bf16 with love.

Original model author: rAIfle

Importance Matrix calculated using groups_merged.txt
92 chunks
n_ctx=512
iMat Calculation uses fp16 precision model weights

Original model README here and below.

Questionable-MN

My last attempt (for now) at beating up Nemo. Done in several steps, but basically it's Nemo-Base, plus bigdata-pw/the-x-files, plus a small private set of RP data and a bit of c2 to finish it up. ChatML.

(Realized I forgot to make this one public, heh. Don't have the settings used for training this anymore, sorry. Anyway, it works. Use standard Nemo sampler settings and whatever sysprompt you feel good about, as usual.)

Downloads last month: 55

GGUF

Model size

12B params

Architecture

llama

Hardware compatibility

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 Quant-Cartel/Questionable-MN-12B-iMat-GGUF

Base model

mistralai/Mistral-Nemo-Base-2407

Finetuned

rAIfle/Questionable-MN-bf16

Quantized

(3)

this model