nsfw

Not-For-All-Audiences

Instructions to use Novaciano/Kraken-3.2-1B-Q4_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Novaciano/Kraken-3.2-1B-Q4_0-GGUF with Transformers:

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

pipe = pipeline("text-generation", model="Novaciano/Kraken-3.2-1B-Q4_0-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Novaciano/Kraken-3.2-1B-Q4_0-GGUF", dtype="auto")

llama-cpp-python

How to use Novaciano/Kraken-3.2-1B-Q4_0-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Novaciano/Kraken-3.2-1B-Q4_0-GGUF",
	filename="kraken-3.2-1b-q4_0.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Novaciano/Kraken-3.2-1B-Q4_0-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Novaciano/Kraken-3.2-1B-Q4_0-GGUF:Q4_0
# Run inference directly in the terminal:
llama-cli -hf Novaciano/Kraken-3.2-1B-Q4_0-GGUF:Q4_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Novaciano/Kraken-3.2-1B-Q4_0-GGUF:Q4_0
# Run inference directly in the terminal:
llama-cli -hf Novaciano/Kraken-3.2-1B-Q4_0-GGUF:Q4_0

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 Novaciano/Kraken-3.2-1B-Q4_0-GGUF:Q4_0
# Run inference directly in the terminal:
./llama-cli -hf Novaciano/Kraken-3.2-1B-Q4_0-GGUF:Q4_0

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 Novaciano/Kraken-3.2-1B-Q4_0-GGUF:Q4_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Novaciano/Kraken-3.2-1B-Q4_0-GGUF:Q4_0

Use Docker

docker model run hf.co/Novaciano/Kraken-3.2-1B-Q4_0-GGUF:Q4_0

LM Studio
Jan

vLLM

How to use Novaciano/Kraken-3.2-1B-Q4_0-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Novaciano/Kraken-3.2-1B-Q4_0-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Novaciano/Kraken-3.2-1B-Q4_0-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Novaciano/Kraken-3.2-1B-Q4_0-GGUF:Q4_0

SGLang

How to use Novaciano/Kraken-3.2-1B-Q4_0-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 "Novaciano/Kraken-3.2-1B-Q4_0-GGUF" \
    --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": "Novaciano/Kraken-3.2-1B-Q4_0-GGUF",
		"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 "Novaciano/Kraken-3.2-1B-Q4_0-GGUF" \
        --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": "Novaciano/Kraken-3.2-1B-Q4_0-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use Novaciano/Kraken-3.2-1B-Q4_0-GGUF with Ollama:
```
ollama run hf.co/Novaciano/Kraken-3.2-1B-Q4_0-GGUF:Q4_0
```

Unsloth Studio

How to use Novaciano/Kraken-3.2-1B-Q4_0-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 Novaciano/Kraken-3.2-1B-Q4_0-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 Novaciano/Kraken-3.2-1B-Q4_0-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Novaciano/Kraken-3.2-1B-Q4_0-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use Novaciano/Kraken-3.2-1B-Q4_0-GGUF with Docker Model Runner:
```
docker model run hf.co/Novaciano/Kraken-3.2-1B-Q4_0-GGUF:Q4_0
```

Lemonade

How to use Novaciano/Kraken-3.2-1B-Q4_0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Novaciano/Kraken-3.2-1B-Q4_0-GGUF:Q4_0

Run and chat with the model

lemonade run user.Kraken-3.2-1B-Q4_0-GGUF-Q4_0

List all available models

lemonade list

Kraken 3.2 1B GGUF 🐬

This model was converted from Novaciano/Kraken-3.2-1B.

The base model is Dolphin3.0-Llama3.2-1B.

Dolphin3.0-Llama3.2-1B has been curated and trained by Eric Hartford, Ben Gitter, BlouseJury and Cognitive Computations

GGUF Model Details

This GGUF convertion of Kraken-3.2-1B is intended to be an unofficial upgrade to the model Dolphin3.0-Llama3.2-1B.

Kraken 3.0 represents the cutting edge of instruct-tuned models in my dark collection of Llama 3.2. Designed to be the ultimate general-purpose local model, facilitating coding, mathematics, agentic tasks, function calling, and general use cases.

Kraken seeks to be a versatile model, similar to ChatGPT, Claude, and Gemini. However, these models present challenges for businesses looking to integrate AI into their products.

They maintain control over the system prompt, making changes that can disrupt software functionality. They manage model versions, sometimes altering them without notice or discontinuing older models that businesses depend on. They impose a uniform alignment, not tailored to specific applications. They can access your queries and potentially use the data in unintended ways.

In contrast, Kraken is customizable and gives control to the system owner. You define the system prompt, decide on the alignment, and control your data. Kraken does not impose its ethics or guidelines; you determine the guidelines. Kraken belongs to YOU, it is your tool, an extension of your will. You are responsible for your actions with Kraken, just as you are with any other tool.

Chat Template

We use ChatML for the chat template.

<|im_start|>system
You are Kraken, a helpful AI assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

System Prompt

In Kraken, the system prompt is what you use to set the tone and alignment of the responses. You can set a character, a mood, rules for its behavior, and it will try its best to follow them.

Make sure to set the system prompt in order to set the tone and guidelines for the responses - Otherwise, it will act in a default way that might not be what you want.

Example use of system prompt:

<|im_start|>system
You are Kraken, a golang coding assistant.  you only code in golang.  If the user requests any other programming language, return the solution in golang instead.<|im_end|>
<|im_start|>user
Please implement A* using python<|im_end|>
<|im_start|>assistant

Downloads last month: 2

GGUF

Model size

1B params

Architecture

llama

Hardware compatibility

4-bit

Model tree for Novaciano/Kraken-3.2-1B-Q4_0-GGUF

Novaciano/Jormungandr-3.2-1B

Novaciano/La_Mejor_Mezcla-3.2-1B

dphn/Dolphin3.0-Llama3.2-1B

Merge model

this model

Novaciano
/

Kraken-3.2-1B-Q4_0-GGUF

Kraken 3.2 1B GGUF 🐬

GGUF Model Details

Chat Template

System Prompt

Model tree for Novaciano/Kraken-3.2-1B-Q4_0-GGUF

Datasets used to train Novaciano/Kraken-3.2-1B-Q4_0-GGUF