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North-ML1
/
Aurora-One-Main

Text Generation
GGUF
English
qwen3
chatml
causal-lm
aurora-one
aurora-ai
aurora-model
aurora-llm
north-ml
northml
language-model
large-language-model
llm
ai-model
chat-model
assistant-model
conversational-ai
generative-ai
openai-compatible
api-compatible
custom-llm
proprietary-model
research-model
experimental-ai
developer-ai
coding-assistant
code-generation
reasoning-model
instruction-following
chat-completion
completion-model
transformer
neural-network
machine-learning
deep-learning
nlp
natural-language-processing
text-ai
ai-assistant
smart-assistant
question-answering
qa-model
knowledge-model
prompting
prompt-engineering
system-prompt
developer-tools
devtools
ai-runtime
model-runtime
inference-api
fast-inference
low-latency
api-endpoint
cloud-ai
hosted-model
model-serving
ml-serving
inference-server
custom-api
north-api
aurora-api
aurora-family
foundation-model
small-language-model
slm
compact-llm
efficient-ai
lightweight-model
edge-ai
local-ai
server-ai
gpu-inference
cuda
benchmarking
evals
model-evaluation
accuracy-testing
gsm8k
gpqa
swe-bench
coding-benchmark
math-reasoning
logic-reasoning
instruction-tuned
fine-tuned
alignment
safe-ai
helpful-ai
agentic-ai
tool-use
function-calling
json-mode
structured-output
markdown-generation
readme-generator
chatbot
ai-chatbot
virtual-assistant
automation
productivity-ai
developer-preview
beta-model
next-gen-ai
future-ai
conversational
Model card Files Files and versions
xet
Community

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

  • Libraries
  • llama-cpp-python

    How to use North-ML1/Aurora-One-Main with llama-cpp-python:

    # !pip install llama-cpp-python
    
    from llama_cpp import Llama
    
    llm = Llama.from_pretrained(
    	repo_id="North-ML1/Aurora-One-Main",
    	filename="aurora-one-generalization-repair-v4-f16.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 North-ML1/Aurora-One-Main 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/Aurora-One-Main:F16
    # Run inference directly in the terminal:
    llama cli -hf North-ML1/Aurora-One-Main:F16
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf North-ML1/Aurora-One-Main:F16
    # Run inference directly in the terminal:
    llama cli -hf North-ML1/Aurora-One-Main:F16
    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/Aurora-One-Main:F16
    # Run inference directly in the terminal:
    ./llama-cli -hf North-ML1/Aurora-One-Main:F16
    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/Aurora-One-Main:F16
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf North-ML1/Aurora-One-Main:F16
    Use Docker
    docker model run hf.co/North-ML1/Aurora-One-Main:F16
  • LM Studio
  • Jan
  • vLLM

    How to use North-ML1/Aurora-One-Main with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "North-ML1/Aurora-One-Main"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "North-ML1/Aurora-One-Main",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/North-ML1/Aurora-One-Main:F16
  • Ollama

    How to use North-ML1/Aurora-One-Main with Ollama:

    ollama run hf.co/North-ML1/Aurora-One-Main:F16
  • Unsloth Studio

    How to use North-ML1/Aurora-One-Main 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/Aurora-One-Main 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/Aurora-One-Main 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/Aurora-One-Main to start chatting
  • Atomic Chat new
  • Docker Model Runner

    How to use North-ML1/Aurora-One-Main with Docker Model Runner:

    docker model run hf.co/North-ML1/Aurora-One-Main:F16
  • Lemonade

    How to use North-ML1/Aurora-One-Main with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull North-ML1/Aurora-One-Main:F16
    Run and chat with the model
    lemonade run user.Aurora-One-Main-F16
    List all available models
    lemonade list
Aurora-One-Main
1.17 GB
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History: 6 commits
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arthu1
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  • aurora-one-generalization-repair-v4-f16.gguf
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  • aurora-one-generalization-repair-v4-lmstudio-f16.gguf
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