Instructions to use theNovaAI/Supernova-experimental-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use theNovaAI/Supernova-experimental-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("theNovaAI/Supernova-experimental-GGUF", dtype="auto")

llama-cpp-python

How to use theNovaAI/Supernova-experimental-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="theNovaAI/Supernova-experimental-GGUF",
	filename="Supernova-experimental-Q3_K_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 theNovaAI/Supernova-experimental-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf theNovaAI/Supernova-experimental-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf theNovaAI/Supernova-experimental-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf theNovaAI/Supernova-experimental-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf theNovaAI/Supernova-experimental-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 theNovaAI/Supernova-experimental-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf theNovaAI/Supernova-experimental-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 theNovaAI/Supernova-experimental-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf theNovaAI/Supernova-experimental-GGUF:Q4_K_M

Use Docker

docker model run hf.co/theNovaAI/Supernova-experimental-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use theNovaAI/Supernova-experimental-GGUF with Ollama:
```
ollama run hf.co/theNovaAI/Supernova-experimental-GGUF:Q4_K_M
```

Unsloth Studio

How to use theNovaAI/Supernova-experimental-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 theNovaAI/Supernova-experimental-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 theNovaAI/Supernova-experimental-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for theNovaAI/Supernova-experimental-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use theNovaAI/Supernova-experimental-GGUF with Docker Model Runner:
```
docker model run hf.co/theNovaAI/Supernova-experimental-GGUF:Q4_K_M
```

Lemonade

How to use theNovaAI/Supernova-experimental-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull theNovaAI/Supernova-experimental-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Supernova-experimental-GGUF-Q4_K_M

List all available models

lemonade list

Supernova-experimental

Quantized to GGUF using llama.cpp

This is an experimental model that was created for the development of NovaAI.

Good at chatting and some RP.

Prompt Template: Alpaca

Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{prompt}

### Response:

Models Merged

The following models were included in the merge:

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	59.79
AI2 Reasoning Challenge (25-Shot)	63.05
HellaSwag (10-Shot)	83.66
MMLU (5-Shot)	56.59
TruthfulQA (0-shot)	49.37
Winogrande (5-shot)	77.35
GSM8k (5-shot)	28.73

Downloads last month: 30

GGUF

Model size

13B params

Architecture

llama

Hardware compatibility

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for theNovaAI/Supernova-experimental-GGUF

PygmalionAI/pygmalion-2-13b

Undi95/Amethyst-13B

Merge model

this model

Collection including theNovaAI/Supernova-experimental-GGUF

Supernova

Collection

Stable and tested series of models • 3 items • Updated Feb 1, 2025

Evaluation results

normalized accuracy on AI2 Reasoning Challenge (25-Shot)
test set Open LLM Leaderboard

63.050
normalized accuracy on HellaSwag (10-Shot)
validation set Open LLM Leaderboard

83.660
accuracy on MMLU (5-Shot)
test set Open LLM Leaderboard

56.590
mc2 on TruthfulQA (0-shot)
validation set Open LLM Leaderboard

49.370
accuracy on Winogrande (5-shot)
validation set Open LLM Leaderboard

77.350
accuracy on GSM8k (5-shot)
test set Open LLM Leaderboard

28.730