Mistral-Nemo-Inst-2407-12B-Thinking-Uncensored-HERETIC-HI-Claude-Opus-mlx-fp16Alexgusevski
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12B Params FP8 Inference Available

The alexgusevski/Mistral-Nemo-Inst-2407-12B-Thinking-Uncensored-HERETIC-HI-Claude-Opus-mlx-fp16 is a 12 billion parameter language model, converted to MLX format from DavidAU's original model. It supports a 32768 token context length. This model is designed for general text generation and understanding tasks, leveraging its base architecture for broad applicability. Its primary use case is within MLX-powered applications, offering efficient inference on Apple silicon.

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Parameters:12BContext length:32kArchitecture:TransformerPrecision:FP8Quantized variants:AvailableLast updated:January 2026
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alexgusevski/Mistral-Nemo-Inst-2407-12B-Thinking-Uncensored-HERETIC-HI-Claude-Opus-mlx-fp16
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.

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top_p

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

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top_k

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

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frequency_penalty

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

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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.

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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.

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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.

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