Instructions to use North-ML1/Forge-1-Mini-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use North-ML1/Forge-1-Mini-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="North-ML1/Forge-1-Mini-GGUF", filename="Forge-1-Mini-F16.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use North-ML1/Forge-1-Mini-GGUF 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/Forge-1-Mini-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf North-ML1/Forge-1-Mini-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf North-ML1/Forge-1-Mini-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf North-ML1/Forge-1-Mini-GGUF:Q4_K_M
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/Forge-1-Mini-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf North-ML1/Forge-1-Mini-GGUF:Q4_K_M
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/Forge-1-Mini-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf North-ML1/Forge-1-Mini-GGUF:Q4_K_M
Use Docker
docker model run hf.co/North-ML1/Forge-1-Mini-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use North-ML1/Forge-1-Mini-GGUF with Ollama:
ollama run hf.co/North-ML1/Forge-1-Mini-GGUF:Q4_K_M
- Unsloth Studio
How to use North-ML1/Forge-1-Mini-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 North-ML1/Forge-1-Mini-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 North-ML1/Forge-1-Mini-GGUF 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/Forge-1-Mini-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use North-ML1/Forge-1-Mini-GGUF with Docker Model Runner:
docker model run hf.co/North-ML1/Forge-1-Mini-GGUF:Q4_K_M
- Lemonade
How to use North-ML1/Forge-1-Mini-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull North-ML1/Forge-1-Mini-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Forge-1-Mini-GGUF-Q4_K_M
List all available models
lemonade list
Forge 1 Mini GGUF
GGUF builds for North-ML1/Forge-1-Mini.
Use the embedded ChatML template and stop on <|im_end|>.
Modern llama.cpp conversation mode:
llama-cli -m Forge-1-Mini-Q4_K_M.gguf -cnv -p "Hi" -st -n 64 --temp 0
The GGUF metadata explicitly sets tokenizer.ggml.eot_token_id=5, where token 5 is <|im_end|>.
from llama_cpp import Llama
llm = Llama(model_path="Forge-1-Mini-Q4_K_M.gguf", n_ctx=512)
out = llm.create_chat_completion(
messages=[{"role": "user", "content": "What is 2 + 2?"}],
max_tokens=96,
temperature=0.0,
stop=["<|im_end|>"],
)
print(out["choices"][0]["message"]["content"].strip())
Expected output:
4
Files
| File | Quantization | Size |
|---|---|---|
Forge-1-Mini-F16.gguf |
F16 | 9.9 MB |
Forge-1-Mini-Q8_0.gguf |
Q8_0 | 5.3 MB |
Forge-1-Mini-Q4_K_M.gguf |
Q4_K_M | 3.8 MB |
Forge-1-Mini-Q3_K_M.gguf |
Q3_K_M | 3.1 MB |
Forge-1-Mini-Q2_K.gguf |
Q2_K | 2.9 MB |
Forge-1-Mini-TQ1_0.gguf |
TQ1_0 | 2.9 MB |
Verification
All listed GGUF files were generated with llama.cpp llama-quantize and passed a llama-cpp-python smoke test using llama.cpp tokenization and greedy sampling:
Who are you? -> I am Forge-1-Mini, a tiny local assistant created by Arthur / North ML.
Hi -> Hi! I am Forge-1-Mini. How can I help?
What is 2 + 2? -> 4
Write a Python function that adds two numbers. -> def add(a, b): return a + b
Who is Jesus? -> Christians believe Jesus Christ is the eternal Son of God...
How should I treat someone I disagree with? -> Treat the person with dignity...
Note: this model has a 192-wide hidden dimension. Some K-quant and TQ tensors fall back to compatible GGML tensor types because those formats require 256-column divisibility. The files are valid GGUF outputs from llama.cpp and were tested after quantization.
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