metadata
license: mit
datasets:
- nlpai-lab/kullm-v2
- mncai/ultrafeedback_binarized_cleaned-ko
Developed by chPark
Training Strategy
We fine-tuned this model based on yanolja/KoSOLAR-10.7B-v0.1 We applied a DPO to realPCH/kosolra-kullm
Run the model
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "realPCH/kosolra_SFT_DPO_v0"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
text = "[INST] Put instruction here. [/INST]"
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=20)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))