Text Generation
Transformers
Safetensors
PEFT
English
mathematics
conjectures
theorem-proving
reasoning
qlora
lora
formal-math
lean
research
conversational
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
File size: 461 Bytes
95d8f84 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"model_type": "peft",
"architectures": [
"PeftModelForCausalLM"
],
"base_model_name_or_path": "Qwen/Qwen2.5-0.5B-Instruct",
"peft_type": "LORA",
"task_type": "CAUSAL_LM",
"_note": "Top-level config.json kept for Hugging Face default download-stats query file counting.",
"parameter_counts": {
"total_params": 502830976,
"trainable_params": 8798208,
"frozen_params": 494032768,
"trainable_ratio": 0.017497346861940342
}
}
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