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@@ -43,21 +43,21 @@ We used the gradient SLURP method.
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  - **Model Type:** SauerkrautLM-7b-HerO is an auto-regressive language model based on the transformer architecture
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- - **Language(s):** English
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  - **License:** APACHE 2.0
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  - **Contact:** [Website](https://vago-solutions.de/#Kontakt) [David Golchinfar](mailto:golchinfar@vago-solutions.de)
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  **Prompt Template:**
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  ```
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  <|im_start|>system
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- You are Sauerkraut-HerO, a great language model that answers politely and competently. Write down your thoughts step by step to solve problems meaningfully.
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  <|im_end|>
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  <|im_start|>user
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- How are you?<|im_end|>
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  <|im_start|>assistant
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- I am doing well!<|im_end|>
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  <|im_start|>user
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- Please tell me about how merged models can benefit from existent top-models.<|im_end|>
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  <|im_start|>assistant
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  ```
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  ## Evaluation
 
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  - **Model Type:** SauerkrautLM-7b-HerO is an auto-regressive language model based on the transformer architecture
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+ - **Language(s):** English, German
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  - **License:** APACHE 2.0
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  - **Contact:** [Website](https://vago-solutions.de/#Kontakt) [David Golchinfar](mailto:golchinfar@vago-solutions.de)
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  **Prompt Template:**
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  ```
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  <|im_start|>system
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+ Du bist Sauerkraut-HerO, ein großes Sprachmodell, das höflich und kompetent antwortet. Schreibe deine Gedanken Schritt für Schritt auf, um Probleme sinnvoll zu lösen.
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  <|im_end|>
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  <|im_start|>user
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+ Wie geht esd dir?<|im_end|>
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  <|im_start|>assistant
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+ Mir geht es gut!<|im_end|>
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  <|im_start|>user
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+ Bitte erkläre mir, wie die Zusammenführung von Modellen durch bestehende Spitzenmodelle profitieren kann.<|im_end|>
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  <|im_start|>assistant
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  ```
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  ## Evaluation