Instructions to use taeminlee/kogpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use taeminlee/kogpt2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="taeminlee/kogpt2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("taeminlee/kogpt2") model = AutoModelForCausalLM.from_pretrained("taeminlee/kogpt2") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use taeminlee/kogpt2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "taeminlee/kogpt2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "taeminlee/kogpt2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/taeminlee/kogpt2
- SGLang
How to use taeminlee/kogpt2 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 "taeminlee/kogpt2" \ --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": "taeminlee/kogpt2", "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 "taeminlee/kogpt2" \ --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": "taeminlee/kogpt2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use taeminlee/kogpt2 with Docker Model Runner:
docker model run hf.co/taeminlee/kogpt2
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Check out the documentation for more information.
KoGPT2-Transformers
KoGPT2 on Huggingface Transformers
KoGPT2-Transformers
SKT-AI μμ 곡κ°ν KoGPT2 (ver 1.0)λ₯Ό Transformersμμ μ¬μ©νλλ‘ νμμ΅λλ€.
SKT-AI μμ KoGPT2 2.0μ 곡κ°νμμ΅λλ€. https://huggingface.co/skt/kogpt2-base-v2/
Demo
- μΌμ λν μ±λ΄ : http://demo.tmkor.com:36200/dialo
- νμ₯ν 리뷰 μμ± : http://demo.tmkor.com:36200/ctrl
Example
from transformers import GPT2LMHeadModel, PreTrainedTokenizerFast
model = GPT2LMHeadModel.from_pretrained("taeminlee/kogpt2")
tokenizer = PreTrainedTokenizerFast.from_pretrained("taeminlee/kogpt2")
input_ids = tokenizer.encode("μλ
", add_special_tokens=False, return_tensors="pt")
output_sequences = model.generate(input_ids=input_ids, do_sample=True, max_length=100, num_return_sequences=3)
for generated_sequence in output_sequences:
generated_sequence = generated_sequence.tolist()
print("GENERATED SEQUENCE : {0}".format(tokenizer.decode(generated_sequence, clean_up_tokenization_spaces=True)))
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