Instructions to use idah4/etm-korean-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use idah4/etm-korean-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="idah4/etm-korean-tiny", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("idah4/etm-korean-tiny", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use idah4/etm-korean-tiny with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "idah4/etm-korean-tiny" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "idah4/etm-korean-tiny", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/idah4/etm-korean-tiny
- SGLang
How to use idah4/etm-korean-tiny 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 "idah4/etm-korean-tiny" \ --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": "idah4/etm-korean-tiny", "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 "idah4/etm-korean-tiny" \ --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": "idah4/etm-korean-tiny", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use idah4/etm-korean-tiny with Docker Model Runner:
docker model run hf.co/idah4/etm-korean-tiny
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소형 텍스트 디코더 LM
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- 200 MB causal LM trained on Korean web text.
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- 학습 데이터: beomi/kowikitext-qa-ref-detail-preview, HAERAE-HUB/KOREAN-WEBTEXT 일부
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## Example
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```python
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소형 텍스트 디코더 LM
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- 200 MB causal LM trained on Korean web text.
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- 학습 데이터: beomi/kowikitext-qa-ref-detail-preview, HAERAE-HUB/KOREAN-WEBTEXT 일부
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- HAERAE-HUB/KOREAN-WEBTEXT 데이터셋 기준: train_ce 4.934 | val_ce 4.835 | val_ppl 125.79 | d1 1.000 | d2 1.000 | rep 0.000 | char_ppl 26.78
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## Example
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```python
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