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---
license: apache-2.0
datasets:
- argilla/distilabel-intel-orca-dpo-pairs
library_name: transformers
pipeline_tag: text-generation
---
<h1 align="center">🏠 Socials</h1>
<p align="center">
🤗 <a href="https://huggingface.co/VitalContribution" target="_blank">HF Repo</a> • 🐦 <a href="https://twitter.com/VContribution" target="_blank">Twitter</a>
</p>
# Evangelion-7B
<img src="https://cdn-uploads.huggingface.co/production/uploads/63ae02ff20176b2d21669dd6/-si1T5gSSjvg1QlfeFKDf.jpeg" width="500" height="600">
I was just curious to see if something special might happen if one uses:
$$
\text{{high-quality DPO dataset}} + \text{{merge of DPO optimized and non-DPO optimized model}}
$$
The underlying model that I used was `/Weyaxi/OpenHermes-2.5-neural-chat-v3-3-Slerp`.
# Dataset
Dataset: `/argilla/distilabel-intel-orca-dpo-pairs`
The dataset was roughly ~3000 samples but they were high quality (according to the chosen_score).
The following filters were applied to the original dataset:
```python
dataset = dataset.filter(
lambda r:
r["status"] != "tie" and
r["chosen_score"] >= 8 and
not r["in_gsm8k_train"]
)
```
# Chat Template
I decided to go with the ChatML which is used for OpenHermes2.5
By the way I integreated the chat template into the models tokenizer.
```
<|im_start|>system
{system}<|im_end|>
<|im_start|>user
{user}<|im_end|>
<|im_start|>assistant
{asistant}<|im_end|>
``` |