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NorthernTribe-Research
/
math-conjecture-model

Text Generation
Transformers
Safetensors
PEFT
English
mathematics
conjectures
theorem-proving
reasoning
qlora
lora
formal-math
lean
research
conversational
Model card Files Files and versions
xet
Community

Instructions to use NorthernTribe-Research/math-conjecture-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use NorthernTribe-Research/math-conjecture-model with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="NorthernTribe-Research/math-conjecture-model")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoModelForCausalLM
    model = AutoModelForCausalLM.from_pretrained("NorthernTribe-Research/math-conjecture-model", dtype="auto")
  • PEFT

    How to use NorthernTribe-Research/math-conjecture-model with PEFT:

    Task type is invalid.
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use NorthernTribe-Research/math-conjecture-model with vLLM:

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

    How to use NorthernTribe-Research/math-conjecture-model 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 "NorthernTribe-Research/math-conjecture-model" \
        --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": "NorthernTribe-Research/math-conjecture-model",
    		"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 "NorthernTribe-Research/math-conjecture-model" \
            --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": "NorthernTribe-Research/math-conjecture-model",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
  • Docker Model Runner

    How to use NorthernTribe-Research/math-conjecture-model with Docker Model Runner:

    docker model run hf.co/NorthernTribe-Research/math-conjecture-model
math-conjecture-model / scripts
109 kB
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  • 1 contributor
History: 6 commits
NorthernTribe-Research's picture
NorthernTribe-Research
Add tailored from-scratch training stack (tokenizer + random-init LM) for math conjecture solving
e69a71a verified about 2 months ago
  • eval_sota.py
    20 kB
    Retarget model to math-conjecture solver profile; remove DeepSeek configs and legacy sync snapshot about 2 months ago
  • merge_and_push.py
    4.64 kB
    Retarget model to math-conjecture solver profile; remove DeepSeek configs and legacy sync snapshot about 2 months ago
  • train_scratch.py
    23.2 kB
    Add tailored from-scratch training stack (tokenizer + random-init LM) for math conjecture solving about 2 months ago
  • train_sft.py
    19.1 kB
    Retarget model to math-conjecture solver profile; remove DeepSeek configs and legacy sync snapshot about 2 months ago
  • train_sota.py
    42.6 kB
    Retarget model to math-conjecture solver profile; remove DeepSeek configs and legacy sync snapshot about 2 months ago