Instructions to use Skywork/Skywork-13B-Math with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Skywork/Skywork-13B-Math with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Skywork/Skywork-13B-Math", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Skywork/Skywork-13B-Math", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Skywork/Skywork-13B-Math with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Skywork/Skywork-13B-Math" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Skywork/Skywork-13B-Math", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Skywork/Skywork-13B-Math
- SGLang
How to use Skywork/Skywork-13B-Math 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 "Skywork/Skywork-13B-Math" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Skywork/Skywork-13B-Math", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "Skywork/Skywork-13B-Math" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Skywork/Skywork-13B-Math", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Skywork/Skywork-13B-Math with Docker Model Runner:
docker model run hf.co/Skywork/Skywork-13B-Math
Download pytorch_model-00024-of-00053.bin from Skywork/Skywork-13B-Math: direct link, hf CLI and curl.
- Browser
- Download file 510 MB
-
https://huggingface.co/Skywork/Skywork-13B-Math/resolve/main/pytorch_model-00024-of-00053.bin
- Command line
-
hf download hf://Skywork/Skywork-13B-Math/pytorch_model-00024-of-00053.bin
-
curl -L -o pytorch_model-00024-of-00053.bin https://huggingface.co/Skywork/Skywork-13B-Math/resolve/main/pytorch_model-00024-of-00053.bin
510 MB
- Xet hash:
- 7b727672ef9abb2454d5273d514ba4407fdc99a5c2ebf22bfd6e8f73f88a9138
- Size of remote file:
- 510 MB
- SHA256:
- 547b76a45fd1471f7dc391ec5e7c083ab5ae658bde51d2ab450c526404e0593a
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