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metadata
language:
  - en
datasets:
  - kyujinpy/orca_math_dpo
pipeline_tag: text-generation
license: cc-by-nc-sa-4.0

Sakura-SOLRCA-Math-Instruct-DPO-v2

Model Details

Model Developers Kyujin Han (kyujinpy)

Method
Using DPO method.
With Intel/orca_dpo_pairs and argilla/distilabel-math-preference-dpo.

I shared the merge version kyujinpy/orca_math_dpo.

I will share the information about my model. (training and code)
Please see: ⭐Sakura-SOLAR(will update).

Model Benchmark

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Model Average ARC HellaSwag MMLU TruthfulQA Winogrande GSM8K
Sakura-SOLRCA-Math-Instruct-DPO-v2 NaN NaN NaN NaN NaN NaN NaN
Sakura-SOLRCA-Math-Instruct-DPO-v1 NaN NaN NaN NaN NaN NaN NaN
Sakura-SOLRCA-Instruct-DPO NaN NaN NaN NaN NaN NaN NaN
Sakura-SOLAR-Instruct-DPO-v2 NaN NaN NaN NaN NaN NaN NaN
Sakura-SOLAR-Instruct-DPO-v1 NaN NaN NaN NaN NaN NaN NaN
kyujinpy/Sakura-SOLAR-Instruct NaN NaN NaN NaN NaN NaN NaN

Implementation Code

### KO-Platypus
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

repo = "kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v2"
OpenOrca = AutoModelForCausalLM.from_pretrained(
        repo,
        return_dict=True,
        torch_dtype=torch.float16,
        device_map='auto'
)
OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)