ChaoticNeutrals/KukulStanta-7B
ChaoticNeutrals/KukulStanta-7B is a 7 billion parameter multimodal language model with a 4096-token context length, developed by ChaoticNeutrals. This model integrates vision capabilities, allowing it to process and understand image inputs. It is specifically designed for applications requiring both text and visual comprehension, demonstrating competitive performance across various benchmarks including reasoning and common sense tasks.
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KukulStanta-7B: A Multimodal Vision-Capable LLM
ChaoticNeutrals/KukulStanta-7B is a 7 billion parameter language model distinguished by its multimodal vision capabilities. This model can process and interpret image inputs, making it suitable for applications that require understanding both textual and visual information. To leverage its vision functionality, users must employ the latest versions of Koboldcpp and load the corresponding mmproj file, which is included in the model repository.
Key Performance Metrics
Evaluated on the Open LLM Leaderboard, KukulStanta-7B demonstrates solid performance across a range of benchmarks:
- Avg. Score: 70.95
- AI2 Reasoning Challenge (25-Shot): 68.43
- HellaSwag (10-Shot): 86.37
- MMLU (5-Shot): 65.00
- TruthfulQA (0-shot): 62.19
- Winogrande (5-shot): 80.03
- GSM8k (5-shot): 63.68
These scores indicate its proficiency in reasoning, common sense, and general language understanding tasks. Detailed evaluation results are available on the Hugging Face Open LLM Leaderboard.
Ideal Use Cases
This model is particularly well-suited for:
- Multimodal applications: Tasks requiring the integration of text and image understanding.
- Reasoning and common sense tasks: Its benchmark performance suggests strong capabilities in these areas.
- Interactive AI systems: Where visual context enhances conversational or analytical abilities.