Instructions to use zzunyang/KLQD_ko_sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use zzunyang/KLQD_ko_sft with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("SEOKDONG/llama3.1_korean_v1.1_sft_by_aidx") model = PeftModel.from_pretrained(base_model, "zzunyang/KLQD_ko_sft") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from zzunyang/KLQD_ko_sft: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/zzunyang/KLQD_ko_sft/resolve/main/tokenizer.json
- Command line
-
hf download hf://zzunyang/KLQD_ko_sft/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/zzunyang/KLQD_ko_sft/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 6ea1d3dbef4c6d40adf4d89b3710e7066c49e165d123c7099c3e0f472485044a
- Size of remote file:
- 17.2 MB
- SHA256:
- ba19762206096696d014df688461f5df1a219bc0d06c503def002279428e3342
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