Arcee-SuperNova-Medius is a 14.8 billion parameter language model developed by Arcee.ai, built on the Qwen2.5-14B-Instruct architecture. This model leverages a cross-architecture distillation pipeline, combining knowledge from Qwen2.5-72B-Instruct and Llama-3.1-405B-Instruct to achieve high-quality instruction-following and complex reasoning. It is optimized for business use cases like customer support, content creation, and technical assistance, offering advanced capabilities in a resource-efficient package.
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arcee-ai/SuperNova-MediusMost 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.