We’ve just released the DoCoreAI Dynamic Temperature Dataset on Hugging Face!
Why is This Dataset Important?
LLMs traditionally operate with fixed temperature settings, which can result in suboptimal responses depending on the task. DoCoreAI dynamically adjusts temperature based on the intelligence scope required, leading to more precise, creative, and context-aware outputs.
What’s Inside?
- Standard & DoCoreAI-optimized responses for various prompts
- The exact temperature values dynamically assigned by DoCoreAI
- A structured format to analyze how temperature impacts AI behavior
Who Should Check This Out?
- LLM researchers studying prompt optimization**
- Developers building AI-powered applications
- Benchmarking enthusiasts looking to compare static vs. dynamic temperatures**
We’d love your feedback & contributions!
Try it out, test different models, and share your insights. If you have ideas for improvements or new benchmarks, feel free to open a discussion or issue.
Ref: Github DoCoreAI
- Let’s collaborate to push AI optimization forward!
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