Instructions to use v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use v000000/NM-12B-Lyris-dev-2-Q6_K-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 v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF:Q6_K
# Run inference directly in the terminal:
llama cli -hf v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF:Q6_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF:Q6_K
# Run inference directly in the terminal:
llama cli -hf v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF:Q6_K

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 v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF:Q6_K
# Run inference directly in the terminal:
./llama-cli -hf v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF:Q6_K

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 v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF:Q6_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF:Q6_K

Use Docker

docker model run hf.co/v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF:Q6_K

LM Studio
Jan
Ollama
How to use v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF with Ollama:
```
ollama run hf.co/v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF:Q6_K
```
Unsloth Desktop
Docker Model Runner
How to use v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF with Docker Model Runner:
```
docker model run hf.co/v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF:Q6_K
```

Lemonade

How to use v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull v000000/NM-12B-Lyris-dev-2-Q6_K-GGUF:Q6_K

Run and chat with the model

lemonade run user.NM-12B-Lyris-dev-2-Q6_K-GGUF-Q6_K

List all available models

lemonade list

Atomic Chat

NM-12B-Lyris-dev-2-Q6_K-GGUF / lyris_dev_2-q6_k.gguf

v000000

Upload lyris_dev_2-q6_k.gguf with huggingface_hub

307ed37 verified about 2 years ago

Download

History Blame GGUF Editor new Delete

10.1 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:: 6e32f64250a1b2e5bd4a0ad0263241ccb15595f4d840cafcf592269155c9045c
Size of remote file:: 10.1 GB
SHA256:: 4004de597a48053ac5167d0c56aff561d9064da5b23af86ffb26ba3fc8613113

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