Instructions to use EasthShin/Youth_Chatbot_Kogpt2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use EasthShin/Youth_Chatbot_Kogpt2-base with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="EasthShin/Youth_Chatbot_Kogpt2-base")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("EasthShin/Youth_Chatbot_Kogpt2-base")
model = AutoModelForCausalLM.from_pretrained("EasthShin/Youth_Chatbot_Kogpt2-base")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use EasthShin/Youth_Chatbot_Kogpt2-base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "EasthShin/Youth_Chatbot_Kogpt2-base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "EasthShin/Youth_Chatbot_Kogpt2-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/EasthShin/Youth_Chatbot_Kogpt2-base

SGLang

How to use EasthShin/Youth_Chatbot_Kogpt2-base 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 "EasthShin/Youth_Chatbot_Kogpt2-base" \
    --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": "EasthShin/Youth_Chatbot_Kogpt2-base",
		"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 "EasthShin/Youth_Chatbot_Kogpt2-base" \
        --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": "EasthShin/Youth_Chatbot_Kogpt2-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use EasthShin/Youth_Chatbot_Kogpt2-base with Docker Model Runner:
```
docker model run hf.co/EasthShin/Youth_Chatbot_Kogpt2-base
```

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Check out the documentation for more information.

Youth_Chatbot_KoGPT2-base

Demo Web: Ainize Endpoint
Demo Web Code: Github
Youth-Chatbot API: Ainize API

Overview

Language model: KoGPT2
Language: Korean
Training data: Aihub

Usage

from transformers import PreTrainedTokenizerFast, GPT2LMHeadModel
U_TKN = '<usr>'
S_TKN = '<sys>'
MASK = '<unused0>'
SENT = '<unused1>'
tokenizer = PreTrainedTokenizerFast.from_pretrained("EasthShin/Youth_Chatbot_Kogpt2-base",
  bos_token='</s>', eos_token='</s>', unk_token='<unk>',
  pad_token='<pad>', mask_token=MASK)

model = GPT2LMHeadModel.from_pretrained('EasthShin/Youth_Chatbot_Kogpt2-base')
input_ids = tokenizer.encode(U_TKN + {your text} + sent + S_TKN)
gen_ids = model.generate(torch.tensor([input_ids]),
                                 max_length=128,
                                 repetition_penalty= 2.0,
                                 pad_token_id=tokenizer.pad_token_id,
                                 eos_token_id=tokenizer.eos_token_id,
                                 bos_token_id=tokenizer.bos_token_id,
                                 use_cache=True)

generated = tokenizer.decode(gen_ids[0, :].tolist())

print(generated)

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