Instructions to use North-ML1/proto-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use North-ML1/proto-mini with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="North-ML1/proto-mini",
	filename="character_bigram_llama.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 North-ML1/proto-mini 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 North-ML1/proto-mini
# Run inference directly in the terminal:
llama cli -hf North-ML1/proto-mini

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf North-ML1/proto-mini
# Run inference directly in the terminal:
llama cli -hf North-ML1/proto-mini

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 North-ML1/proto-mini
# Run inference directly in the terminal:
./llama-cli -hf North-ML1/proto-mini

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 North-ML1/proto-mini
# Run inference directly in the terminal:
./build/bin/llama-cli -hf North-ML1/proto-mini

Use Docker

docker model run hf.co/North-ML1/proto-mini

LM Studio
Jan
Ollama
How to use North-ML1/proto-mini with Ollama:
```
ollama run hf.co/North-ML1/proto-mini
```

Unsloth Studio

How to use North-ML1/proto-mini 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 North-ML1/proto-mini 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 North-ML1/proto-mini to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for North-ML1/proto-mini to start chatting

Atomic Chat new
Docker Model Runner
How to use North-ML1/proto-mini with Docker Model Runner:
```
docker model run hf.co/North-ML1/proto-mini
```

Lemonade

How to use North-ML1/proto-mini with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull North-ML1/proto-mini

Run and chat with the model

lemonade run user.proto-mini-{{QUANT_TAG}}

List all available models

lemonade list

Proto Mini - Random models that output text

Proto-mini are small GGUF files that output text - without needing to be trained on huge corpus'. Via lite pretraining - random init - and more, we have achieved quality that beats init models. If you cpt on these GGUF's via Unsloth Studio, you get sequence level text generations.

It reaches speeds on 640 tok/s on the content in init.txt, random tokens with c at the start.

It already has the vocab - it just needs to know what to use.

Downloads last month: 66

GGUF

Model size

1.38M params

Architecture

llama

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

Inference Providers NEW

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