Instructions to use mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use mradermacher/NemoDori-v0.2.2-12B-MN-ties-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 mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/NemoDori-v0.2.2-12B-MN-ties-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 mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/NemoDori-v0.2.2-12B-MN-ties-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 mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf mradermacher/NemoDori-v0.2.2-12B-MN-ties-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 mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF:Q4_K_M

Use Docker

docker model run hf.co/mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF with Ollama:
```
ollama run hf.co/mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF with Docker Model Runner:
```
docker model run hf.co/mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF:Q4_K_M
```

Lemonade

How to use mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mradermacher/NemoDori-v0.2.2-12B-MN-ties-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.NemoDori-v0.2.2-12B-MN-ties-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

NemoDori-v0.2.2-12B-MN-ties-GGUF / NemoDori-v0.2.2-12B-MN-ties.IQ4_XS.gguf

mradermacher

uploaded from nethype/kaos

cb7ac96 verified about 2 years ago

Download

History Blame GGUF Editor new Delete

6.8 GB

This file is stored with Xet . It is too big to display, but you can still download it.

Xet Pointer Details

( Raw pointer file )

Xet hash:: dce97ba9e5d91d2abc7f2a113f629c64d48c91e550521adc98a3f2baf798a6f5
Size of remote file:: 6.8 GB
SHA256:: 29822d0cf172baa51adbc8d02f6bc72abc954bebcfce6541b283e7d63f38e156

Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.