EldritchLabs/MN-12B-Mag-Mell-R1-Uncensored-Scale1.2
MN-12B-Mag-Mell-R1-Uncensored-Scale1.2 is a 12 billion parameter language model developed by EldritchLabs, based on the Naphula/MN-12B-Mag-Mell-R1-Uncensored model. It features a context length of 32768 tokens and is specifically optimized with a scale of 1.2, which is noted as a sweet spot for Nemo models. This uncensored model is designed for applications requiring unrestricted content generation and potentially enhanced intelligence compared to its predecessor.
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MN-12B-Mag-Mell-R1-Uncensored-Scale1.2 Overview
EldritchLabs' MN-12B-Mag-Mell-R1-Uncensored-Scale1.2 is a 12 billion parameter language model derived from the Naphula/MN-12B-Mag-Mell-R1-Uncensored base. This iteration maintains the uncensored nature of its predecessor while introducing a key modification: a scale factor of 1.2. This specific scaling is highlighted as an optimal configuration for Nemo-based models, aiming to deliver improved performance.
Key Capabilities
- Unrestricted Content Generation: Designed to produce uncensored outputs, suitable for use cases requiring broad content flexibility.
- Optimized Performance: Utilizes a 1.2 scale factor, which is identified as a "sweet spot" for Nemo models, potentially leading to enhanced intelligence and efficiency.
- Large Context Window: Supports a context length of 32768 tokens, enabling processing of extensive inputs and generating coherent long-form content.
Good For
- Applications requiring a highly flexible and uncensored language model.
- Scenarios where the 1.2 scale factor might offer a performance advantage over other scaling configurations.
- Tasks benefiting from a substantial context window for complex or lengthy interactions.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.