North open-source in June-July
Collection
3 items • Updated
How to use North-ML1/proto-mini with llama.cpp:
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
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
# 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
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
docker model run hf.co/North-ML1/proto-mini
How to use North-ML1/proto-mini with Ollama:
ollama run hf.co/North-ML1/proto-mini
How to use North-ML1/proto-mini with Unsloth Studio:
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
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
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for North-ML1/proto-mini to start chatting
How to use North-ML1/proto-mini with Docker Model Runner:
docker model run hf.co/North-ML1/proto-mini
How to use North-ML1/proto-mini with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull North-ML1/proto-mini
lemonade run user.proto-mini-{{QUANT_TAG}}lemonade list
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.
We're not able to determine the quantization variants.