SteelSkull's L3.1-MS-Astoria-70b-v2 is a 70 billion parameter language model built on the Llama 3.1 architecture, featuring a 32K context window. This model stock merge aims to combine the robust storytelling capabilities of multiple base models while maintaining high intelligence. It is designed for complex narrative generation and general-purpose conversational AI, supporting both Llama 3 and 'meth' instruction formats.
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L3.1-MS-Astoria-70b-v2: Merged Storytelling and Intelligence
L3.1-MS-Astoria-70b-v2 is a 70 billion parameter model developed by SteelSkull, based on the Llama 3.1 architecture. This model represents a "model stock" merge, combining several Llama 3.1-based models to achieve a balance between robust storytelling and general intelligence. It leverages a 32,768-token context window, making it suitable for extended conversations and complex narrative generation.
Key Capabilities
- Enhanced Storytelling: Designed to integrate the narrative strengths of multiple models, aiming for coherent and engaging long-form content.
- Maintained Intelligence: Focuses on preserving the core intelligence of its constituent Llama 3.1 models.
- Flexible Instruction Formats: Supports both the standard Llama 3 instruction format and a specialized "meth" format for stepped thinking, particularly useful when Llama 3's default behavior is insufficient.
- Model Stock Merge: Built from a diverse set of Llama 3.1-70B models, including
mlabonne/Llama-3.1-70B-Instruct-lorablated,migtissera/Tess-3-Llama-3.1-70B,NeverSleep/Lumimaid-v0.2-70B,Sao10K/L3.1-70B-Euryale-v2.2, andArliAI/Llama-3.1-70B-ArliAI-RPMax-v1.2, andnbeerbower/Llama3.1-Gutenberg-Doppel-70B.
Good For
- Applications requiring advanced narrative generation and creative writing.
- Use cases benefiting from a large context window for detailed interactions.
- Developers seeking a model that balances creative output with strong reasoning capabilities.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.