Downloads · 30 days
8
2% of all-time downloads
tellang/yeji-8b-rslora-v7
yeji-8b-rslora-v7 is a text generation model from tellang. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
한국어 운세/점술 도메인 특화 8B LLM. Qwen3-8B-Base 기반 RSLoRA 파인튜닝.
Downloads · 30 days
8
2% of all-time downloads
All-time downloads
428
Public
Parameters
8.2B
16.4 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors16.4 GB · 100%
From the Hugging Face model README
한국어 운세/점술 도메인 특화 8B LLM. Qwen3-8B-Base 기반 RSLoRA 파인튜닝.
YEJI 프로젝트의 8B 주력 모델입니다. Qwen3-8B-Base를 RSLoRA (Rank-Stabilized LoRA)로 파인튜닝하여 사주, 점성술, 타로, 화투 4개 도메인에서 전문 상담 능력을 갖추었습니다.
| Version | Base | Method | Params | Status |
|---|---|---|---|---|
| v1 | Qwen3-8B | QDoRA | 8.2B | Deprecated |
| v2 | Qwen3-8B | QLoRA | 8.2B | Deprecated |
| v4 | Qwen3-8B | RSLoRA + T-Shirt | 8.2B | Deprecated |
| v7 | Qwen3-8B | RSLoRA | 8.2B | Stable |
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "tellang/yeji-8b-rslora-v7"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto", device_map="auto")
messages = [
{"role": "system", "content": "당신은 전문 사주 상담사입니다."},
{"role": "user", "content": "1997년 10월 24일생의 올해 운세를 봐주세요."}
]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.7)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
| Format | Model | Use Case |
|---|---|---|
| AWQ 4-bit | yeji-8b-rslora-v7-AWQ | vLLM 서빙 |
| Model | Params | Status |
|---|---|---|
| yeji-4b-instruct-v9 | 4.0B | Latest |
| yeji-4b-instruct-v9-AWQ | ~1.3B | Production |