Instructions to use plasmova/nova-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use plasmova/nova-v3 with Transformers:

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

pipe = pipeline("text-generation", model="plasmova/nova-v3", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("plasmova/nova-v3", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use plasmova/nova-v3 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 plasmova/nova-v3:F16
# Run inference directly in the terminal:
llama cli -hf plasmova/nova-v3:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf plasmova/nova-v3:F16
# Run inference directly in the terminal:
llama cli -hf plasmova/nova-v3:F16

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 plasmova/nova-v3:F16
# Run inference directly in the terminal:
./build/bin/llama cli -hf plasmova/nova-v3:F16

Use Docker

docker model run hf.co/plasmova/nova-v3:F16

Llama new
LM Studio
Jan

vLLM

How to use plasmova/nova-v3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "plasmova/nova-v3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "plasmova/nova-v3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/plasmova/nova-v3:F16

SGLang

How to use plasmova/nova-v3 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 "plasmova/nova-v3" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "plasmova/nova-v3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "plasmova/nova-v3" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "plasmova/nova-v3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use plasmova/nova-v3 with Ollama:
```
ollama run hf.co/plasmova/nova-v3:F16
```
Unsloth Desktop
Docker Model Runner
How to use plasmova/nova-v3 with Docker Model Runner:
```
docker model run hf.co/plasmova/nova-v3:F16
```

Lemonade

How to use plasmova/nova-v3 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull plasmova/nova-v3:F16

Run and chat with the model

lemonade run user.nova-v3-F16

List all available models

lemonade list

Atomic Chat

nova-v3

File size: 591 Bytes

{
  "architectures": [
    "NovaForCausalLM"
  ],
  "dtype": "float32",
  "eos_token_id": 10,
  "head_dim": 64,
  "hidden_size": 640,
  "intermediate_size": 1920,
  "max_position_embeddings": 2048,
  "model_type": "nova",
  "num_attention_heads": 10,
  "num_hidden_layers": 26,
  "num_key_value_heads": 5,
  "pad_token_id": 10,
  "rope_theta": 100000.0,
  "transformers_version": "4.57.5",
  "use_cache": true,
  "vocab_size": 32768,
  "auto_map": {
    "AutoConfig": "configuration_nova.NovaConfig",
    "AutoModelForCausalLM": "modeling_nova.NovaForCausalLM"
  }
}