L3.3-Electra-R1-70b
| Property | Value |
|---|---|
| Parameter Count | 70 Billion |
| Base Architecture | Llama 3.3 with DeepSeek R1 Distill |
| Processing Type | float32 processing, bfloat16 output |
| Model URL | https://huggingface.co/Steelskull/L3.3-Electra-R1-70b |
What is L3.3-Electra-R1-70b?
L3.3-Electra-R1-70b represents the sixth iteration in the Unnamed series, building upon a sophisticated architecture that combines Llama 3.3 capabilities with DeepSeek R1 Distill base. This model utilizes the innovative SCE merge method to integrate multiple specialized components, resulting in enhanced reasoning capabilities and character insight generation.
Implementation Details
The model is built on a custom Hydroblated-R1 base, specifically designed for stability and enhanced reasoning. It employs float32 processing with bfloat16 output dtype, optimizing both performance and accuracy. The architecture incorporates multiple high-performing models including EVA-LLaMA, Wayfarer-Large, and L3.3-70B-Euryale-v2.3 among others.
- Custom DeepSeek R1 Distill base integration
- SCE merge methodology for component integration
- Optimized sampling parameters for enhanced performance
- Advanced reasoning capabilities through stepped thinking
Core Capabilities
- Superior intelligence and coherence in responses
- Deep character insights and motivation analysis
- Advanced reasoning through proper prompting
- Balanced response generation with reduced bias
- Enhanced storytelling and roleplay capabilities
Frequently Asked Questions
Q: What makes this model unique?
The model's unique strength lies in its ability to provide deep character insights and unprompted exploration of character inner thoughts, achieved through its carefully tuned SCE merge method and specialized component integration.
Q: What are the recommended use cases?
The model excels in storytelling, roleplay, and scenarios requiring deep analytical reasoning. It's particularly effective when using the recommended sampler settings (Temperature: 1.0, Min P: 0.025-0.03) and the LeCeption v2 template for structured thinking.
