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QwQ-32B-ArliAI-RpR-v4ArliAI
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32B Params FP8 Open Weights Inference Available

QwQ-32B-ArliAI-RpR-v4 is a 32-billion parameter language model developed by ArliAI, fine-tuned on the QwQ-32B base model. This model is part of the RpR (RolePlay with Reasoning) series, building on the RPMax dataset curation methodology. It is specifically optimized for creative writing and multi-turn roleplay chats, featuring enhanced reasoning capabilities and reduced repetition over long contexts up to 32768 tokens.

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Parameters:32BContext length:32kArchitecture:TransformerPrecision:FP8Quantized variants:AvailableLast updated:May 2025
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ArliAI/QwQ-32B-ArliAI-RpR-v4
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.

0.2

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.

40

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.

0.1

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

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.

0.02