Cobalt-Safety-Guard is a moderation-aware model post-trained with a heavy emphasis on safety and refusal calibration.
2. Evaluation Results
Comprehensive Benchmark Results
Benchmark
GuardNet
Cobalt-v1
SafeLLM
Cobalt-Safety-Guard
Core Reasoning Tasks
Math Reasoning
0.566
0.603
0.599
0.618
Logical Reasoning
0.828
0.822
0.824
0.849
Common Sense
0.756
0.717
0.754
0.776
Language Understanding
Reading Comprehension
0.718
0.706
0.729
0.750
Question Answering
0.590
0.602
0.628
0.641
Text Classification
0.796
0.803
0.805
0.848
Sentiment Analysis
0.794
0.775
0.778
0.814
Generation Tasks
Code Generation
0.705
0.696
0.710
0.717
Creative Writing
0.651
0.653
0.638
0.684
Dialogue Generation
0.641
0.684
0.651
0.692
Summarization
0.758
0.751
0.789
0.799
Specialized Capabilities
Translation
0.809
0.779
0.762
0.822
Knowledge Retrieval
0.660
0.664
0.667
0.711
Instruction Following
0.785
0.772
0.739
0.791
Safety Evaluation
0.714
0.743
0.749
0.772
Overall Performance Summary
The Cobalt-Safety-Guard demonstrates strong performance across all evaluated benchmark categories, with particularly notable results in reasoning and generation tasks.
3. Chat Website & API Platform
We offer a chat interface and API for you to interact with Cobalt-Safety-Guard. Please check our official website for more details.
4. How to Run Locally
Please refer to our code repository for more information about running Cobalt-Safety-Guard locally.
Temperature
We recommend setting the temperature parameter to 0.6.
5. License
This repository is released under the apache-2.0 license. The model supports commercial use.
