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12B Params FP8 Open Weights Inference Available

allura-org/MN-12b-RP-Ink is a 12 billion parameter LoRA fine-tune of Mistral Nemo Instruct, specifically optimized for roleplay-focused generative tasks. This model leverages a unique and diverse dataset, drawing inspiration from methodologies used in models like SorcererLM and Slush. With a 32768 token context length, it excels at generating creative and engaging narrative content for roleplaying scenarios.

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Parameters:12BContext length:32kArchitecture:TransformerPrecision:FP8Quantized variants:AvailableLast updated:December 2024
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allura-org/MN-12b-RP-Ink
Popular Sampler Settings

Most commonly used values from Featherless users

temperature

This setting influences the sampling randomness. Lower values make the model more deterministic; higher values introduce randomness. Zero is greedy sampling.

1.03

top_p

This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.

0.9

top_k

This limits the number of top tokens to consider. Set to -1 to consider all tokens.

197

frequency_penalty

This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.

–

presence_penalty

This setting penalizes new tokens based on their presence in the generated text so far. Values > 0 encourage new tokens; < 0 encourages repetition.

0.15

repetition_penalty

This setting penalizes new tokens based on their appearance in the prompt and generated text. Values > 1 encourage new tokens; < 1 encourages repetition.

1.1

min_p

This setting representing the minimum probability for a token to be considered relative to the most likely token. Must be in [0, 1]. Set to 0 to disable.

0.05