Instructions to use sapie-model/SQL-sft-grpo-5000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sapie-model/SQL-sft-grpo-5000 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sapie-model/SQL-sft-grpo-5000", device_map="auto") - PEFT
How to use sapie-model/SQL-sft-grpo-5000 with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
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Download README.md from sapie-model/SQL-sft-grpo-5000: direct link, hf CLI and curl.
- Browser
- Download file 793 Bytes
-
https://huggingface.co/sapie-model/SQL-sft-grpo-5000/resolve/main/README.md
- Command line
-
hf download hf://sapie-model/SQL-sft-grpo-5000/README.md
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curl -L -o README.md https://huggingface.co/sapie-model/SQL-sft-grpo-5000/resolve/main/README.md
793 Bytes
metadata
library_name: transformers
license: apache-2.0
language:
- ko
tags:
- lora
- peft
- adapters
task_categories:
- text-generation
base_model: OpenPipe/gemma-3-27b-it-text-only
sapie-model/SQL-sft-grpo-5000
- ์ด ๋ฆฌํฌ๋ LoRA/์ด๋ํฐ ๊ฐ์ค์น๋ง ํฌํจํฉ๋๋ค. ์ถ๋ก ์์๋ ๋ฒ ์ด์ค ๋ชจ๋ธ
OpenPipe/gemma-3-27b-it-text-only๊ณผ ํจ๊ป ๋ก๋ํ์ธ์.
์ฌ์ฉ ์์
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
base = "OpenPipe/gemma-3-27b-it-text-only"
model_id = "sapie-model/SQL-sft-grpo-5000" # ์ด ์ด๋ํฐ ๋ฆฌํฌ
tok = AutoTokenizer.from_pretrained(base)
model = AutoModelForCausalLM.from_pretrained(base, torch_dtype='auto', device_map='auto')
model = PeftModel.from_pretrained(model, model_id)