Instructions to use QuantFactory/mistral-nemo-cc-12B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use QuantFactory/mistral-nemo-cc-12B-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("QuantFactory/mistral-nemo-cc-12B-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use QuantFactory/mistral-nemo-cc-12B-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 QuantFactory/mistral-nemo-cc-12B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantFactory/mistral-nemo-cc-12B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf QuantFactory/mistral-nemo-cc-12B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantFactory/mistral-nemo-cc-12B-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/mistral-nemo-cc-12B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/mistral-nemo-cc-12B-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/mistral-nemo-cc-12B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/mistral-nemo-cc-12B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/mistral-nemo-cc-12B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use QuantFactory/mistral-nemo-cc-12B-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/mistral-nemo-cc-12B-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use QuantFactory/mistral-nemo-cc-12B-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/mistral-nemo-cc-12B-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/mistral-nemo-cc-12B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/mistral-nemo-cc-12B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.mistral-nemo-cc-12B-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

QuantFactory/mistral-nemo-cc-12B-GGUF

This is quantized version of nbeerbower/mistral-nemo-cc-12B created using llama.cpp

Original Model Card

mistral-nemo-cc-12B

nbeerbower/mistral-nemo-gutenberg-12B-v3 finetuned on flammenai/casual-conversation-DPO.

This is an experimental finetune that formats the conversation data sequentially with ChatML.

Method

Finetuned using an A100 on Google Colab for 3 epochs.

Fine-tune Llama 3 with ORPO

Downloads last month: 129

GGUF

Model size

12B params

Architecture

llama

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/mistral-nemo-cc-12B-GGUF

Base model

intervitens/mini-magnum-12b-v1.1

Finetuned

nbeerbower/mistral-nemo-gutenberg-12B-v3

Quantized

(4)

this model

QuantFactory
/

mistral-nemo-cc-12B-GGUF

QuantFactory/mistral-nemo-cc-12B-GGUF

Original Model Card

mistral-nemo-cc-12B

Method

Model tree for QuantFactory/mistral-nemo-cc-12B-GGUF

Dataset used to train QuantFactory/mistral-nemo-cc-12B-GGUF