Instructions to use mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF", dtype="auto")

llama-cpp-python

How to use mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF",
	filename="Aronnax-N9Bv2-1.0.i1-IQ1_M.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 mradermacher/Aronnax-N9Bv2-1.0-i1-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/Aronnax-N9Bv2-1.0-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/Aronnax-N9Bv2-1.0-i1-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/Aronnax-N9Bv2-1.0-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf mradermacher/Aronnax-N9Bv2-1.0-i1-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/Aronnax-N9Bv2-1.0-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf mradermacher/Aronnax-N9Bv2-1.0-i1-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/Aronnax-N9Bv2-1.0-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF:Q4_K_M

Use Docker

docker model run hf.co/mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF:Q4_K_M

SGLang

How to use mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF with Ollama:
```
ollama run hf.co/mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF:Q4_K_M
```

Unsloth Studio

How to use mradermacher/Aronnax-N9Bv2-1.0-i1-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 mradermacher/Aronnax-N9Bv2-1.0-i1-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 mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF with Docker Model Runner:
```
docker model run hf.co/mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF:Q4_K_M
```

Lemonade

How to use mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Aronnax-N9Bv2-1.0-i1-GGUF-Q4_K_M

List all available models

lemonade list

mradermacher commited on Jan 19

Commit

d879239

verified ·

1 Parent(s): 2d067e1

auto-patch README.md

Browse files

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README.md +64 -0

README.md CHANGED Viewed

@@ -1,3 +1,23 @@
 <!-- ### quantize_version: 2 -->
 <!-- ### output_tensor_quantised: 1 -->
 <!-- ### convert_type: hf -->
@@ -7,3 +27,47 @@
 <!-- ### quants_skip:  -->
 <!-- ### skip_mmproj:  -->
 weighted/imatrix quants of https://huggingface.co/Mitchins/Aronnax-N9Bv2-1.0

+---
+base_model: Mitchins/Aronnax-N9Bv2-1.0
+language:
+- en
+library_name: transformers
+license: apache-2.0
+model_name: Aronnax-N9Bv2-1.0
+mradermacher:
+  readme_rev: 1
+quantized_by: mradermacher
+tags:
+- text-generation
+- literary
+- prose
+- creative-writing
+- narrative
+- nemotron
+---
+## About
 <!-- ### quantize_version: 2 -->
 <!-- ### output_tensor_quantised: 1 -->
 <!-- ### convert_type: hf -->
 <!-- ### quants_skip:  -->
 <!-- ### skip_mmproj:  -->
 weighted/imatrix quants of https://huggingface.co/Mitchins/Aronnax-N9Bv2-1.0
+<!-- provided-files -->
+***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Aronnax-N9Bv2-1.0-i1-GGUF).***
+static quants are available at https://huggingface.co/mradermacher/Aronnax-N9Bv2-1.0-GGUF
+## Usage
+If you are unsure how to use GGUF files, refer to one of [TheBloke's
+READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
+more details, including on how to concatenate multi-part files.
+## Provided Quants
+(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
+| Link | Type | Size/GB | Notes |
+|:-----|:-----|--------:|:------|
+| [GGUF](https://huggingface.co/mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF/resolve/main/Aronnax-N9Bv2-1.0.imatrix.gguf) | imatrix | 0.1 | imatrix file (for creating your own quants) |
+| [GGUF](https://huggingface.co/mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF/resolve/main/Aronnax-N9Bv2-1.0.i1-IQ1_S.gguf) | i1-IQ1_S | 4.9 | for the desperate |
+| [GGUF](https://huggingface.co/mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF/resolve/main/Aronnax-N9Bv2-1.0.i1-IQ3_XS.gguf) | i1-IQ3_XS | 5.2 |  |
+| [GGUF](https://huggingface.co/mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF/resolve/main/Aronnax-N9Bv2-1.0.i1-Q4_K_S.gguf) | i1-Q4_K_S | 6.3 | optimal size/speed/quality |
+| [GGUF](https://huggingface.co/mradermacher/Aronnax-N9Bv2-1.0-i1-GGUF/resolve/main/Aronnax-N9Bv2-1.0.i1-Q6_K.gguf) | i1-Q6_K | 9.2 | practically like static Q6_K |
+Here is a handy graph by ikawrakow comparing some lower-quality quant
+types (lower is better):
+![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
+And here are Artefact2's thoughts on the matter:
+https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
+## FAQ / Model Request
+See https://huggingface.co/mradermacher/model_requests for some answers to
+questions you might have and/or if you want some other model quantized.
+## Thanks
+I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
+me use its servers and providing upgrades to my workstation to enable
+this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
+<!-- end -->