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README.md

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 license: cc-by-nc-4.0
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+language:
+- en
+- de
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- finetune
+- dpo
+- Instruct
+- augmentation
+- german
+datasets:
+- argilla/distilabel-math-preference-dpo
+---
+
+![SauerkrautLM](https://vago-solutions.de/wp-content/uploads/2023/12/sauerkrautlm-solar.png "SauerkrautLM-SOLAR-Instruct")
+## VAGO solutions SauerkrautLM-SOLAR-Instruct
+Introducing **SauerkrautLM-SOLAR-Instruct** – our Sauerkraut version of the powerful[upstage/SOLAR-10.7B-Instruct-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0) ! 
+Aligned with **DPO**
+
+# Table of Contents
+1. [Overview of all SauerkrautLM-Mixtral models](#all-sauerkrautlm-mixtral-models)
+2. [Model Details](#model-details)
+   - [Prompt template](#prompt-template)
+   - [Training Dataset](#training-dataset)
+   - [Data Contamination Test](#data-contamination-test-results)
+3. [Evaluation](#evaluation)
+5. [Disclaimer](#disclaimer)
+6. [Contact](#contact)
+7. [Collaborations](#collaborations)
+8. [Acknowledgement](#acknowledgement)
+
+
+## All SauerkrautLM-SOLAR-Instruct
+
+| Model | HF    | GPTQ  | GGUF  | AWQ  |
+|-------|-------|-------|-------|-------|
+| SauerkrautLM-SOLAR-Instruct  | [Link](https://huggingface.co/VAGOsolutions/SauerkrautLM-SOLAR-Instruct/) | coming soon | coming soon | coming soon |
+
+## Model Details
+**SauerkrautLM-SOLAR-Instruct**
+- **Model Type:** SauerkrautLM-SOLAR-Instruct is a finetuned Model based on [upstage/SOLAR-10.7B-Instruct-v1.0](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0) 
+- **Language(s):** English, German
+- **License:** cc-by-nc-4.0
+- **Contact:** [Website](https://vago-solutions.de/#Kontakt) [David Golchinfar](mailto:[email protected])
+
+### Training Dataset:
+
+SauerkrautLM-SOLAR-Instruct was trained with mix of German data augmentation and translated data. 
+Aligned through **DPO** with our **new German SauerkrautLM-DPO dataset** based on parts of the SFT SauerkrautLM dataset 
+as chosen answers and [Sauerkraut-7b-HerO](https://huggingface.co/VAGOsolutions/SauerkrautLM-7b-HerO) as rejected answers. Added with additional **translated Parts of the [HuggingFaceH4/ultrafeedback_binarized](https://huggingface.co/datasets/HuggingFaceH4/ultrafeedback_binarized)** (Our dataset do not contain any TruthfulQA prompts - check Data Contamination Test Results) and **[argilla/distilabel-math-preference-dpo](https://huggingface.co/datasets/argilla/distilabel-math-preference-dpo).**  
+We found, that only a simple translation of training data can lead to unnatural German phrasings. 
+Data augmentation techniques were used to grant grammatical, syntactical correctness and a more natural German wording in our training data. 
+
+We improved the German language skills on this model. Nevertheless, certain formulations may occur that are not entirely correct.
+
+
+
+
+
+### Data Contamination Test Results
+
+Some models on the HuggingFace leaderboard had problems with wrong data getting mixed in.
+We checked our SauerkrautLM-DPO dataset with a special test [1] on this model as target model and upstage/SOLAR-10.7B-Instruct-v1.0 as reference model. 
+The HuggingFace team used the same methods [2, 3].
+
+Our results, with `result < 0.1, %:` being well below 0.9, indicate that our dataset is free from contamination.
+
+*The data contamination test results of HellaSwag and Winograde will be added once [1] supports them.*
+
+| Dataset                        | ARC   | MMLU | TruthfulQA | GSM8K |
+|------------------------------|-------|-------|-------|-------|
+| **SauerkrautLM-DPO**| result < 0.1, %: 0.0 |result < 0.1, %: 0.09 | result < 0.1, %: 0.13 | result < 0.1, %: 0.16 |
+
+[1] https://github.com/swj0419/detect-pretrain-code-contamination
+
+[2] https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/474#657f2245365456e362412a06
+
+[3] https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard/discussions/265#657b6debf81f6b44b8966230
+
+### Prompt Template:
+```
+### User:
+Hallo, wie geht es dir?
+
+### Assistant:
+Hallo! Es freut mich, dass du mit mir kommunizierst. Ich bin ein künstlicher Intelligenz-Assistent und ich funktioniere optimal.
+Wie kann ich zu deiner Unterstützung beitragen oder hast du eine Frage, die ich klären sollte? In welcher Art und Weise kann ich dich helfen?
+
+```
+*Prompt Example on Temp 0.3
+
+## Evaluation
+coming soon
+
+## Disclaimer
+We must inform users that despite our best efforts in data cleansing, the possibility of uncensored content slipping through cannot be entirely ruled out.
+However, we cannot guarantee consistently appropriate behavior. Therefore, if you encounter any issues or come across inappropriate content, we kindly request that you inform us through the contact information provided.
+Additionally, it is essential to understand that the licensing of these models does not constitute legal advice. We are not held responsible for the actions of third parties who utilize our models.
+ 
+## Contact
+If you are interested in customized LLMs for business applications, please get in contact with us via our website or contact us at [Dr. Daryoush Vaziri](mailto:[email protected]). We are also grateful for your feedback and suggestions.
+ 
+## Collaborations
+We are also keenly seeking support and investment for our startup, VAGO solutions, where we continuously advance the development of robust language models designed to address a diverse range of purposes and requirements. If the prospect of collaboratively navigating future challenges excites you, we warmly invite you to reach out to us.
+
+## Acknowledgement
+Many thanks to [argilla](https://huggingface.co/datasets/argilla) and [Huggingface](https://huggingface.co) for providing such valuable datasets to the Open-Source community. And of course a big thanks to [upstage](https://huggingface.co/upstage) for providing the open source community with their latest technology!