Steelskull/L3.3-San-Mai-R1-70b

Warm
Public
70B
FP8
32768
License: llama3.3
Hugging Face
Overview

Model Overview

Steelskull's L3.3-San-Mai-R1-70b is the foundational release in a three-part series, named after the Japanese bladesmithing technique "San-Mai" for its balanced approach. This 70 billion parameter model is built on a custom DeepSeek R1 Distill base (DS-Hydroblated-R1-v4.1) and utilizes the SCE merge method to integrate several specialized Llama 3.3-based components.

Key Capabilities

  • Advanced Reasoning: Integrates Cirrus and Hanami elements for enhanced logical processing.
  • Creative Expression & Coherence: Leverages EVA and EURYALE foundations for strong creative output and consistent narrative flow.
  • Detailed Scene Description: Incorporates Anubis components for rich, descriptive outputs.
  • Balanced Responses: Features Negative_LLAMA integration to reduce bias and provide a more balanced perspective.
  • Deep Character Insights: Demonstrates a unique ability to explore character inner thoughts and motivations without explicit prompting.

Performance Highlights

According to UGI-Benchmark results (as of 02/20/2025):

  • UGI Score: 40.04
  • Natural Intelligence: 42.36
  • Willingness Score: 2.5/10 (indicating low refusal rates)
  • Political Lean: -8.5% (Liberalism)

Recommended Use Cases

This model is ideal for applications requiring:

  • Narrative Generation: Excels in creating coherent and insightful stories with deep character development.
  • Complex Conversational AI: Its advanced reasoning and balanced responses make it suitable for nuanced interactions.
  • Role-playing and Creative Writing: The "X-factor" for unprompted character exploration is particularly beneficial here.

Recommended Sampler Settings (by @Geechan)

  • Static Temperature: 1 - 1.05
  • Min P: 0.015
  • DRY Settings (optional): Multiplier 0.8, Base 1.75, Length 4

Prompting Templates

  • LLam@ception: A template by @.konnect for enhanced prompting.
  • LeCeption: A revamped XML version of LLam@ception 1.5.2 by @Steel, featuring stepped thinking and reasoning. It uses <think> and </think> tags for reasoning formatting.