Instructions to use ColoAI/Colo-Math-mini-preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ColoAI/Colo-Math-mini-preview with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-7B-Instruct") model = PeftModel.from_pretrained(base_model, "ColoAI/Colo-Math-mini-preview") - Transformers
How to use ColoAI/Colo-Math-mini-preview with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ColoAI/Colo-Math-mini-preview") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ColoAI/Colo-Math-mini-preview", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use ColoAI/Colo-Math-mini-preview with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ColoAI/Colo-Math-mini-preview" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ColoAI/Colo-Math-mini-preview", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ColoAI/Colo-Math-mini-preview
- SGLang
How to use ColoAI/Colo-Math-mini-preview 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 "ColoAI/Colo-Math-mini-preview" \ --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": "ColoAI/Colo-Math-mini-preview", "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 "ColoAI/Colo-Math-mini-preview" \ --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": "ColoAI/Colo-Math-mini-preview", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ColoAI/Colo-Math-mini-preview with Docker Model Runner:
docker model run hf.co/ColoAI/Colo-Math-mini-preview
| base_model: Qwen/Qwen2-7B-Instruct | |
| library_name: peft | |
| pipeline_tag: text-generation | |
| tags: | |
| - base_model:adapter:Qwen/Qwen2-7B-Instruct | |
| - lora | |
| - transformers | |
| license: apache-2.0 | |
| language: | |
| - en | |
| ## Model Details | |
| ### Model Description | |
| this model is really good at math and can code to get the math answered. | |
| - **Developed by:** [ColoAI] | |
| - **Language(s) (NLP):** [English] | |
| - **License:** [Apache 2.0 license] | |
| - **Finetuned from model:** [qwen2-7b] | |
| ## Uses | |
| this model is only used for math! don't use it for anything else! | |
| ### Out-of-Scope Use | |
| this model cannot, write, chat, or roleplay. only math is used for this model. | |
| - PEFT 0.16.0 |