Instructions to use madatnlp/trinity-kormath with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use madatnlp/trinity-kormath with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="madatnlp/trinity-kormath")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("madatnlp/trinity-kormath") model = AutoModelForCausalLM.from_pretrained("madatnlp/trinity-kormath") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use madatnlp/trinity-kormath with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "madatnlp/trinity-kormath" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "madatnlp/trinity-kormath", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/madatnlp/trinity-kormath
- SGLang
How to use madatnlp/trinity-kormath 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 "madatnlp/trinity-kormath" \ --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": "madatnlp/trinity-kormath", "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 "madatnlp/trinity-kormath" \ --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": "madatnlp/trinity-kormath", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use madatnlp/trinity-kormath with Docker Model Runner:
docker model run hf.co/madatnlp/trinity-kormath
add tokenizer
Browse files- merges.txt +0 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- vocab.json +0 -0
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{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "pad_token": "</s>", "mask_token": "<mask>"}
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{"unk_token": "<|endoftext|>", "bos_token": "<|endoftext|>", "eos_token": "<|endoftext|>", "add_prefix_space": true, "special_tokens_map_file": "/root/.cache/huggingface/transformers/c2ab65b9d700d0871fd407d489869d7b93f69fb5f1a58fb1fac796fd43b9ea27.1f5b09bb43973b9fbd2ba75c9fe44ffab036b980c4e6a9d779aa7707913416fe", "name_or_path": "skt/ko-gpt-trinity-1.2B-v0.5", "tokenizer_class": "GPT2Tokenizer"}
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