DeepHermes 3 - Mistral 24B Preview by Nous Research is a 24 billion parameter language model with a 32768 token context length, uniquely designed to unify both intuitive and long chain-of-thought reasoning modes. This model excels at complex problem-solving by allowing users to toggle deep reasoning via a system prompt, alongside improved LLM annotation, judgment, and function calling capabilities. It is optimized for advanced agentic tasks, multi-turn conversations, and enhanced user steerability.
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NousResearch/DeepHermes-3-Mistral-24B-PreviewMost 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.
top_p
This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.
top_k
This limits the number of top tokens to consider. Set to -1 to consider all tokens.
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.
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.
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.