Instructions to use ModernoTech/Nova-Core with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use ModernoTech/Nova-Core 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 ModernoTech/Nova-Core:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ModernoTech/Nova-Core:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ModernoTech/Nova-Core:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf ModernoTech/Nova-Core:Q4_K_M

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf ModernoTech/Nova-Core:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama cli -hf ModernoTech/Nova-Core:Q4_K_M

Use Docker

docker model run hf.co/ModernoTech/Nova-Core:Q4_K_M

Llama new
LM Studio
Jan

vLLM

How to use ModernoTech/Nova-Core with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ModernoTech/Nova-Core"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ModernoTech/Nova-Core",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ModernoTech/Nova-Core:Q4_K_M

Ollama
How to use ModernoTech/Nova-Core with Ollama:
```
ollama run hf.co/ModernoTech/Nova-Core:Q4_K_M
```
Unsloth Desktop

How to use ModernoTech/Nova-Core with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ModernoTech/Nova-Core:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "ModernoTech/Nova-Core:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use ModernoTech/Nova-Core with Docker Model Runner:
```
docker model run hf.co/ModernoTech/Nova-Core:Q4_K_M
```

Lemonade

How to use ModernoTech/Nova-Core with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ModernoTech/Nova-Core:Q4_K_M

Run and chat with the model

lemonade run user.Nova-Core-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use ModernoTech/Nova-Core with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ModernoTech/Nova-Core:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default ModernoTech/Nova-Core:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use ModernoTech/Nova-Core with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf ModernoTech/Nova-Core:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "ModernoTech/Nova-Core:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Nova Core 2.0

Moderno Tech · Nova Core

Conversational intelligence by Moderno Tech.

Publication status: Foundation distribution under Nova identity
Family: Nova Core · Version 2.0

Download GGUF · Moderno Tech

Nova Core 2.0

Nova Core 2.0 is an official Moderno Tech language model of the Nova family.

This publication establishes Nova Core's commercial identity, repository structure, provenance documentation and distribution under the Moderno Tech brand. The published artifact derives from a Gemma 4 E2B base and is redistributed with the identity, packaging and documentation of Moderno Tech's Nova line, with full attribution to the original authors and licensing terms.

Moderno Tech / Nova identity

Nova Core 2.0 is presented as a Moderno Tech product within the Nova family. The identity, naming, versioning, documentation and repository structure belong to Moderno Tech. The underlying technical provenance is documented separately below.

Product identity

Product name: Nova Core 2.0
Organization: Moderno Tech
Family: Nova Core
Commercial version: 2.0
Base architecture: Gemma 4, dense transformer (Gemma4ForCausalLM-compatible GGUF)
Format: GGUF
Quantization: see published artifact filename
Context size declared by the GGUF: 131072 tokens

Core specifications

Field	Value
Product	Nova Core 2.0
Organization	Moderno Tech
Family	Nova Core
Base architecture	Gemma 4 dense transformer
Parameters (size label from file)	4.6B
Format	GGUF
Context size declared by the GGUF	131,072 tokens
Published artifact	`Nova-Core-1.0-Gemma4-E2B-Q4_K_M.gguf`
Expected bytes	3,009,448,896
SHA-256	`c9213a33b16d513482790bb7092243f783a450e35f7deca584a41e0470afdb97`

About Nova Core

A conversational language model with 131,072 tokens of declared context window, based on the Gemma 4 architecture. It is positioned as the compact reasoning backbone of the Nova line, intended for chat, summarization, technical assistance, and local inference on consumer hardware where the 4.6B-class weights are viable.

Downloads

Variant	File	Format	Approx. size
Foundation distribution	Nova-Core-1.0-Gemma4-E2B-Q4_K_M.gguf	GGUF	2.80 GB

Installation (verified with llama.cpp)

llama-cli -hf ModernoTech/Nova-Core -c 4096 --temp 0.7 --top-p 0.9           -p "Hello, who are you?" -n 128

Adjust -ngl (GPU layers) according to your hardware. On Apple Silicon, raise it gradually. If instability occurs, fall back to -ngl 0 for CPU inference.

Capabilities and limitations

Conversational text generation.
Declared context window: 131,072 tokens (subject to runtime memory).
Base architecture: Gemma 4.
Variant label: 4.6B-class fine-tune as published by the upstream source.
Dense (non-MoE) model — all layers run on each forward pass.
On a 16 GB unified-memory Mac, expect roughly 3 GB RAM for the weights plus context/generation overhead.

Technical provenance and licensing

Commercial product: Modern Tech — Nova Core
Product version: 2.0 (foundation distribution)
Base artifact SHA-256: c9213a33b16d513482790bb7092243f783a450e35f7deca584a41e0470afdb97
Architecture internal identifier in the GGUF metadata: gemma4 (Gemma 4 family)
Parameter count reported by the GGUF itself: 4.6B
Number of transformer blocks: 35
Embedding dimension: 1536
Context length embedded in the GGUF: 131,072
Tensor precision mix: Q4_K/Q3_K/Q6_K plus BF16/F32 norm and embedding tensors

The weights, tokenizer, and architecture are inherited from a third-party Gemma-family checkpoint that was re-branded and packaged by Moderno Tech for the Nova product line. Moderno Tech does not assert original authorship of the pre-trained weights; the model card documents the technical provenance chain.

License: gemma (Gemma Terms of Use, original Google license; see the official Gemma license)
Authorship attribution must remain with the original creators
Moderno Tech package distributed under its packaging brand
Any modification or fine-tuning must be documented in a new version with its own hash

Inspected parameters (verified via GGUF metadata)

Parameter	Value
Architecture	gemma4 (Gemma 4 E2B-class)
Transformer blocks	35
Embedding dim	1536
FFN dim	12288
Attention heads	8
KV heads	1
Shared KV layers	20
Sliding window	512 (sliding) / 131072 (full)
RoPE freq (global)	1,000,000
RoPE freq (sliding)	10,000
BOS token id	2
EOS token id	1
Vocabulary size	262,144
Final logit softcapping	30
Quantization	see local verification (llama-cli reports mixed Q4/Q3/Q6)

Verified runtime behaviour (local M4 test)

$ llama-cli -m nova-2b.gguf -p "Responde solo: Hola, soy Nova." -n 8 --ctx-size 512 -ngl 0
Loading model...
model: nova-2b.gguf
ftype: Q2_K - Medium (reported; quantization actually mixed)
modalities: text
[Start thinking]
1
[ Prompt: 49.5 t/s | Generation: 34.5 t/s ]

Tested on: MacBook Air M4 (unified 16 GB RAM). The numbers above represent this particular test. Other hardware (4 GB Intel Mac, 8 GB Mac, etc.) is untested and may need different -ngl and -c parameters.

Limitations

Dense model: all 35 layers execute on every token. There is no MoE sparsity.
With -ngl 0 (CPU), throughput on ARM/Intel lower than a pure Metal path.
Context window declared: 131,072 tokens. Practical context is bounded by available RAM.
The uncensored variant may produce inappropriate responses. Apply content moderation in downstream applications.
Gemma's original terms impose commercial restrictions (revenue threshold, etc.); verify the Gemma license before redistributing.

Version policy

2.0 (foundation): initial commercial distribution of the verified artifact under Nova branding.
Future 2.1 / 3.0 releases: NW versions will require a new hash, training documentation, provenance and methodology.
Quantizations are distribution variants of the same commercial version.

Institutional footer

MODERNO TECH

Nova AI

Intelligence. Engineering. Innovation.

Moderno Tech: https://www.moderno.com.ar
Hugging Face organization: https://huggingface.co/ModernoTech
Repository: https://huggingface.co/ModernoTech/Nova-Core

Downloads last month: -

GGUF

Model size

5B params

Architecture

gemma4

Hardware compatibility

4-bit