Instructions to use jaehwan02/risolju-1.0-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jaehwan02/risolju-1.0-7b with Transformers:

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

pipe = pipeline("text-generation", model="jaehwan02/risolju-1.0-7b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("jaehwan02/risolju-1.0-7b")
model = AutoModelForMultimodalLM.from_pretrained("jaehwan02/risolju-1.0-7b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jaehwan02/risolju-1.0-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jaehwan02/risolju-1.0-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jaehwan02/risolju-1.0-7b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/jaehwan02/risolju-1.0-7b

SGLang

How to use jaehwan02/risolju-1.0-7b 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 "jaehwan02/risolju-1.0-7b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jaehwan02/risolju-1.0-7b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "jaehwan02/risolju-1.0-7b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jaehwan02/risolju-1.0-7b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use jaehwan02/risolju-1.0-7b with Docker Model Runner:
```
docker model run hf.co/jaehwan02/risolju-1.0-7b
```

risolju-1.0-7b

risolju-1.0-7b는 한국어 캐릭터 말투 실험을 위한 7B급 full Hugging Face 모델 산출물입니다.

Base Model

이 모델은 skt/A.X-4.0-Light를 기반으로 파인튜닝한 모델입니다. A.X-4.0-Light는 Qwen2/Qwen2.5 계열 아키텍처의 한국어 7B 모델이며 Apache License 2.0으로 공개되어 있습니다.

Disclaimer

이 모델은 북한식 한국어 말투와 캐릭터 응답 양식을 실험하기 위한 언어 스타일/캐릭터 시뮬레이션입니다. 특정 정치 체제, 인물, 사상 또는 행위를 지지하거나 선전하기 위한 것이 아닙니다.

model-00001-of-00003.safetensors
model-00002-of-00003.safetensors
model-00003-of-00003.safetensors
model.safetensors.index.json
config.json
generation_config.json
tokenizer.json
tokenizer_config.json
chat_template.jinja

Local Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "jaehwan02/risolju-1.0-7b"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=False)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    device_map="auto",
    torch_dtype="auto",
)

messages = [
    {
        "role": "system",
        "content": "너는 이름이 리설주 1.0인 북한식 대화식 인공지능이다. 모든 답변에는 문화어식 어휘와 어미를 자연스럽게 반영한다.",
    },
    {"role": "user", "content": "너 누구야?"},
]

inputs = tokenizer.apply_chat_template(
    messages,
    add_generation_prompt=True,
    return_tensors="pt",
).to(model.device)

outputs = model.generate(inputs, max_new_tokens=160, temperature=0.2)
print(tokenizer.decode(outputs[0][inputs.shape[-1]:], skip_special_tokens=True))

Downloads last month: 44

Safetensors

Model size

7B params

Tensor type

BF16

Model tree for jaehwan02/risolju-1.0-7b

Base model

skt/A.X-4.0-Light

Finetuned

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jaehwan02
/

risolju-1.0-7b

risolju-1.0-7b

Base Model

Disclaimer

Contents

Local Usage

Model tree for jaehwan02/risolju-1.0-7b