Reasoning and Multilingual Performance

#64
by Cagnicolas - opened

I've been evaluating Gemma-2-9b-it for production deployment and have some questions about its capabilities:

  1. Reasoning Performance: The model card mentions strong reasoning capabilities. Has anyone benchmarked this against GPT-3.5 or similar models on complex reasoning tasks?

  2. Multilingual Support: While English is primary, the model was trained on 8 languages. What's the quality degradation for non-English languages in production use?

  3. Temperature Settings: The documentation recommends lower temperatures (0.3) compared to other models. What's the reasoning behind this, and how does it affect output diversity?

  4. Context Window Management: With the standard context length, what are best practices for handling longer conversations or documents?

  5. Fine-tuning Results: Has anyone successfully fine-tuned this model for domain-specific tasks? What were the results?

Looking forward to hearing from the community about real-world deployment experiences.

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